Overview
MAHARAJA INSTITUTE OF TECHNOLOGY Thandavapura, Nanjangud Taluk571 302 Mysore district, Karnataka, India
Department of Electronics and Communication Engineering
8th semester NOTES Wireless Cellular and LTE 4G Broadband 15EC81 MODULE – 1 CHAPTER 1: Key Enablers for LTE features •
OFDM
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Single carrier FDMA (SCFDMA)
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Single carrier FDE (SCFDE)
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Channel Dependent Multiuser Resource Scheduling
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Multi antenna Techniques
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IP based Flat network Architecture
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LTE Network Architecture (Sec 1.4 1.5 of Text)
CHAPTER 2: Wireless Fundamentals •
Cellular concept
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Broadband wireless channel (BWC)
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Fading in BWC
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Modeling BWC – Empirical and Statistical models
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Mitigation of Narrow band and Broadband Fading (Sec 2.2 – 2.7of Text)
MEGHANA M N ASSISTANT PROFESSOR DEPT. OF ECE
MITT
WIRELESS CELLULAR & LTE 4G BROADBAND – 15EC81
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MODULE 1 CHAPTER 1 – KEY ENABLERS FOR LTE FEATURES
1. EVOLUTION OF MOBILE BROADBAND There are 5 cellular system technologies: 1G, 2G, 3G, 4G and 5G technology.
1.1 FIRST GENERATION (1G) TECHNOLOGY •
1G refers to the firstgeneration.
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It uses analog signal to transmit data.
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It was introduced in early 1980’s and designed exclusively for voice communication.
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AMPS (Advanced Mobile Phone system) standards were the popular 1G cellular system.
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1G data speed is up to 2.4kbps.
Example: cordless mobile system Drawbacks ➢ Poor Voice Quality and Poor Battery Life ➢ Large Phone Size and no Security ➢ no data services and no roaming ➢ Cannot transmit for long distance
1.2 SECOND GENERATION (2G) TECHNOLOGY •
2G refers to the secondgeneration.
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2G technology uses digital signals for first time.
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It was launched in 1991 and used GSM (Global System for Mobile communication) standards.
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2G data speed is up to 64kbps.
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Text(SMS) and multimedia transmission were introduced.
2.5G TECHNOLOGY •
2G technology along with GPRS (General Packet Radio Service) standard give rise to 2.5G technology.
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2.5G enabled roaming, web browsing, email services and fast upload/download speed.
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2G data speed is up to 160kbps.
2.75 G TECHNOLOGIES •
2.75 G launched enhanced GSM standard called EDGE (Enhanced Data for Global Evolution).
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Its supports high data rate of upto 170kbps and it enables multimedia access.
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Example of 2G: Keypad mobiles Drawback of 2G: ➢ Limited data rates ➢ Basically circuit switched system ➢ Not supported for true mobility and less security.
1.3 THIRD GENERATION (3G) TECHNOLOGY •
3G refers to third generation.
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3G technology was introduced in year 2000s.
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Data transmission speed increased from170Kbps to 2Mbps.
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3G Technology uses CDMA( Code Division Multiple Access) – 2000 and UMTS (Universal Mobile Telecommunication System) standards.
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3G facilitates increased bandwidth and data transfer rates.
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Compatible with smart phones and Provides Webbased applications.
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Main characteristics of 3G network is it uses Digital broadband and with more speed.
3.5G TECHNOLOGY •
3.5 G technology was introduced in around 2000s where the evolution of network took next phase from 3G.
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3.5G is capable of using high bit rate than 3G and the new idea of mobility bit rate was introduced.
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The 3 main standards in 3.5G technology are HSDPA (High Speed Datalink Packet Access), HSUPA (High Speed Uplink Packet Access) and HSPA+ (High Speed Packet Access).
Example of 3G: smart phones Drawback of 3G: ➢ Expensive fees for 3G Licenses Services. ➢ It was challenge to build the infrastructure for 3G. ➢ High Bandwidth Requirement. ➢ Expensive 3G Phones. ➢ Large Cell Phones.
1.4 FOURTH GENERATION (4G) TECHNOLOGY •
4G refers to fourth generation.
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4G technology was introduced in year 2004.
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Data transmission speed/ bit rate of 5Mbps to 1000Mbps.
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4G Technology uses LTE (Long Term Evolution) standards.
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It supports mobile web access, cloud computing, global mobility support and high definition mobile TV.
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4G also enable a VOLTE (Voice Over Long Term Evolution) standard for high speed wireless communication for mobile phones and data terminals including IoT devices and wearable.
1.5 FIFTH GENERATION (5G) TECHNOLOGY •
5G refers to fifth generation.
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5G was started from late 2010s.
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Complete wireless communication with almost no limitations.
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It is highly supportable to WWWW (Wireless World Wide Web).
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Aims at higher capacity than current 4G, allowing a higher density of mobile broadband users.
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Supports interactive multimedia, voice streaming and enhanced security.
2. KEY ENABLING TECHNOLOGIES AND FEATURES OF LTE ***** Key Enabling Technologies and Features of LTE are
1. Orthogonal Frequency Division Multiplexing (OFDM) 2. SCFDE and SCFDMA 3. Channel Dependent Multiuser Resource Scheduling 4. Multiantenna Techniques 5. IPBased Flat Network Architecture
2.1 ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING (OFDM) ***** Q.: Explain the advantages of OFDM for LTE. [8M] June/July 2019 •
3G systems are based on CDMA technology. Advantage: CDMA Performs remarkably well for low data rate communications, where a large number of users can be multiplexed to achieve high system capacity. Limitation: CDMA cannot able to handle the large bandwidth required for highspeed applications and hence design becomes complex.
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OFDM has emerged as a technology for achieving high data rates and is widely used in WiFi.
➢ The following advantages of OFDM led to its selection for LTE: ***** 1. Elegant solution to multipath interference: •
The main aim is to achieve high Bitrate transmissions in a wireless channel the critical challenge is Inter Symbol Interference (ISI) caused by multi path.
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At high data rates the symbol time is shorter; hence it only takes a small delay to cause ISI.
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OFDM is a multicarrier modulation technique which can be used to eliminate the ISI effect.
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In OFDM, the subcarriers are orthogonal to one another over the symbol duration.
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Thereby instead of using nonover lapping subcarrier, subcarrier can be overlapped over a channel which eliminates ISI.
2. Reduced computational complexity: •
OFDM can be easily implemented using Fast Fourier Transforms (FFT) at the sender side and Inverse Fast Fourier Transforms (IFFT) at the receiving end.
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The computational complexity of OFDM = (B log B Tm), where B is the bandwidth and Tm is the delay spread.
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Reduced complexity is mainly used the downlink as it simplifies receiver processing and thus reduces mobile device cost and power consumption.
3. Graceful degradation of performance under excess delay: •
The performance of an OFDM system degrades gracefully as the delay spread exceeds the designed value.
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OFDM is well suited for adaptive modulation and coding, which allows the system to make the best use of the available channel conditions.
4. Exploitation of frequency diversity: •
OFDM provides the range of frequencies to subcarriers in the frequency domain, which can provide robustness against errors.
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OFDM also allows scaling of channel bandwidth without affecting the hardware design of the base station and the mobile station.
5. Enables efficient multiaccess scheme: •
OFDM can be used as a multiaccess scheme by partitioning different subcarriers among multiple users.
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This scheme is referred as OFDMA and is used in LTE standard.
6. Robust against narrowband interference: •
OFDM is relatively robust against narrowband interference, since such interference affects only a fraction of the subcarriers.
7. Suitable for coherent demodulation: •
It is relatively easy to do pilotbased channel estimation in OFDM systems, which renders them suitable for coherent demodulation schemes that are more power efficient.
8. Facilitates use of MIMO: •
MIMO refers to a collection of signal processing techniques that use multiple antennas at both the transmitter and receiver to improve system performance.
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For MIMO techniques to be effective, it is required that the channel conditions are such that the multipath
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delays do not cause ISI interference. •
OFDM converts a frequency selective broad band channel into several narrowband flat fading channels where the MIMO models and techniques work well.
9. Efficient support of broadcast services: •
It is possible to operate an OFDM network as a Single Frequency Network (SFN).
• This allows broadcast signals from different cells to combine over the air and which enhances the received signal power, thereby enabling higher data rate broadcast transmissions.
➢ Disadvantages of OFDM: •
PeaktoAverage Ratio (PAR): OFDM has high PAR, which causes nonlinearity and clipping distortion when passed through an RF amplifier.
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High PAR increases the cost of the transmitter.
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OFDM is tolerated in the downlink as part of the design, for the uplink LTE selected a variation of OFDM that has a lower peakto average ratio.
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The modulation used for the uplink is called Single Carrier Frequency Division Multiple Access. (SCFDMA).
2.2 SCFDE and SCFDMA ➢ SingleCarrier Frequency Domain Equalization (SCFDE) •
It is a singlecarrier (SC) modulation combined with frequencydomain equalization (FDE).
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It is an alternative approach to inter symbol interference (ISI) mitigation.
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It uses QAM (Quadrature Amplitude Modulation) rather than FFT/IFFT used in OFDM to send data.
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SCFDE retains all the advantages of OFDM such as multipath resistance and low complexity, while having a low peaktoaverage ratio of 45dB.
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It keeps the mobile station cost down and the battery life up.
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LTE incorporated a SCFDE as a power efficient transmission scheme for the uplink.
➢ SingleCarrier Frequency Division Multiple Access( SCFDMA) •
A multiuser version of SCFDE, called SCFDMA.
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The uplink of LTE implements uses to SCFDMA, which allows multiple users to use parts of the frequency spectrum.
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SCFDMA closely resembles OFDMA and also preserves the PAR properties.
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The drawback of SCFDE is increases the complexity of the transmitter and the receiver.
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2.3 CHANNEL DEPENDENT MULTIUSER RESOURCE SCHEDULING •
Resource scheduling is mainly used in OFDM  Orthogonal Frequency Division Multiplexing and OFDMA  Orthogonal Frequency Division Multiple Access.
Figure 1: Resource mapping in OFDMA
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The OFDMA scheme used in LTE provides more flexibility with respect to channel resources allocation.
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OFDMA allows allocation in both time and frequency and it is possible to design algorithms to allocate resources in a flexible and dynamic manner to meet arbitrary throughput, delay and other requirements.
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The standard supports dynamic, channeldependent scheduling to enhance overall system capacity.
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In OFDM, It is possible to allocate subcarriers among users in such a way that the overall capacity is increased.
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Allocation of subcarriers among users is called as frequency selective multiuser scheduling, which focuses on transmitting power in each user’s best channel portion.
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In OFDMA, frequency selective scheduling can be combined with multiuser time domain scheduling.
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Capacity gains are also obtained by adapting the modulation and coding to the instantaneous signaltonoise ratio conditions for each user subcarrier.
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For highmobility users, OFDMA can be used to achieve frequency diversity by coding and interleaving across subcarriers.
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Frequency diverse scheduling is best suited for control signalling and delay sensitive services.
2.4 MULTIANTENNA TECHNIQUES •
The LTE standard provides multiantenna solutions to improve link robustness, system capacity, and spectral efficiency.
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Multiantenna techniques supported in LTE include: 1.
Transmit diversity
2. Beam forming
3.
Spatial multiplexing
4. Multi user MIMO
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1. TRANSMIT DIVERSITY •
Diversity means send copies of the same signal by using two or more communication channels with different characteristics. This is a technique to prevent multipath fading in the wireless channel. f D(1) Data Symbols D(1)
Transmit Antenna 1
D(0) t
f
D(0)
D(0)*
Transmit Antenna 2
D(1)* t
Figure 2: Transmit diversity (SFBC)
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LTE transmit diversity is based on spacefrequency block coding (SFBC) techniques.
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Transmit diversity is used in common downlink channels that cannot make use of channeldependent scheduling.
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It increases system capacity and cell range.
2. BEAMFORMING •
Multiple antennas in LTE may also be used beamforming technique to transmit the beam in the direction of the receiver and away from interference, thereby improving the received signaltointerference ratio.
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It can provide significant improvements in coverage range, capacity, reliability, and battery life.
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It can also be useful in providing angular information for user tracking.
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LTE supports beamforming in the downlink.
3. SPATIAL MULTIPLEXING •
In spatial multiplexing, multiple independent streams can be transmitted in parallel over multiple antennas and can be separated at the receiver using multiple receive chains through appropriate signal processing.
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Spatial multiplexing provides data rate and capacity gains proportional to the number of antennas used.
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It works well under good SNR and light load conditions. LTE standard supports spatial multiplexing with up to four transmits antennas and four receiver antennas.
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MIMO with Transmit diversity
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MIMO with Spatial Multiplexing
Figure 3: Comparison of MIMO with Diversity and spatial multiplexing
4. MULTIUSER MIMO •
Since spatial multiplexing requires multiple transmit antennas, it is currently not supported in the uplink due to complexity and high cost.
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MultiUser MIMO (MUMIMO) allows multiple users in the uplink, each with a single antenna, to transmit using the same frequency and time.
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The signals from the different MUMIMO users are separated at the base station receiver using accurate channel state information of each user obtained through uplink reference signals that are orthogonal between users.
Figure 4: Comparison between Single and multiuser MIMO
2.5 IPBASED FLAT LTE SAE NETWORK ARCHITECTURE**** Q.: Explain flat LTE SAE architecture. [8M] June/July 2019 •
Apart from air interface the other aspects of LTE is Flat Network Architecture. Flat implies fewer nodes and less hierarchical structure for the network which reduces the infrastructure cost.
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It also means fewer interfaces and protocolrelated processing and reduced interoperability testing, which lowers the development cost.
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Fewer nodes also allow better optimization of radio interface, merging of some control plane protocols, and short session startup time.
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Figure 5 shows how the 3GPP network architecture evolution.
Figure 5: 3GPP evolution toward a flat LTE SAE architecture
➢
Flat LTE architecture description
• 3GPP Release 6 architecture has four network elements in the data path: Base Station (BS), Radio Network Controller (RNC), Serving GPRS Service Node (SGSN), and Gateway GRPS Service Node (GGSN). •
Release 7 introduced a direct tunnel option from the RNC to GGSN, which eliminated SGSN from the data path.
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LTE on the other hand, will have only two network elements in the data path: the enhanced NodeBore (eNodeB) and a System Architecture Evolution Gateway (SAEGW).
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LTE merges the BS and RNC functionality into a single unit.
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The control path includes a functional entity called the Mobility Management Entity (MME), which provides control plane functions related to subscriber, mobility, and session management.
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The MME and SAEGW collocated in a single entity called the Access Gateway (AGW).
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A key aspect of the LTE flat architecture is that all services, including voice, are supported on the IP packet network using IP protocols.
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Whereas previous 2G and 3G systems had a separate circuitswitched subnetwork for supporting voice with their own Mobile Switching Centers (MSC) and transport networks.
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LTE focuses on a single Evolved Packet Core (EPC) over which all services are supported, which could provide huge operational and infrastructure cost savings.
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However, LTE has been designed for IP services with a flat architecture, due to backwards compatibility reasons certain legacy, nonIP aspects of the 3GPP architecture such as the GPRS tunnelling protocol and PDCP (Packet Data Convergence Protocol) still exists within the LTE network architecture.
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3. LTE NETWORK ARCHITECTURE*** Q.: Explain LTE network architecture or Evolved Packet Core architecture in LTE. [8M] • The core network design by 3GPP Release 8 to support LTE is called the Evolved Packet Core (EPC). • EPC is designed to provide a high capacity, reduced latency and supports all IPs. • Flat architecture reduces cost and supports advanced realtime operations. It is designed not only to support LTE, but also provide interworking with legacy 2G GERAN and 3G UTRAN networks connected via SGSN.
➢ Functions of LTE architecture •
It includes access control, packet routing and transfer, mobility management, security, radio resource management and network management.
➢ LTE architectural elements The EPC includes four new elements: 1. Serving Gateway (SGW) 2. Packet Data Network Gateway (PGW) 3. Mobility Management Entity (MME) 4. Policy and Charging Rules Function (PCRF) •
Figure 6 shows the endtoend architecture of EPC used in LTE.
Figure 6: Evolved Packet Core architecture
1. SERVING GATEWAY (SGW) •
SGW terminates the interface toward the 3GPP radio access networks.
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It acts as an interface between the RAN and core network, and manages user plane mobility.
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SGW is incorporated in downlink packet buffering and initiation of networktriggered service request procedures.
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Other functions of SGW include: 
Lawful interception, packet routing and forwarding.

Transport level packet marking in the uplink and the downlink.

Accounting support for user and interoperator charging.
2. PACKET DATA NETWORK GATEWAY (PGW) •
It controls IP data services, does routing, allocates IP addresses, enforces policy, and provides access for non3GPP access networks.
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The PGW acts as the termination point of the EPC toward other Packet Data Networks (PDN) such as the Internet, private IP network, or the IMS network providing enduser services.
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It serves as an anchor point for sessions toward external PDN and provides functions such as user IP address allocation, policy enforcement, packet filtering, and charging support.
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Policy enforcement includes operatordefined rules for resource allocation to control data rate, QoS, and usage.
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Packet filtering functions include deep packet inspection for application detection.
3. MOBILITY MANAGEMENT ENTITY (MME) •
The MME performs the signaling and control functions to manage the user terminal access to network connections, assignment of network resources.
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Mobility management function such as idle mode location tracking, paging, roaming, and handovers.
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MME controls all control plane functions related to subscriber and session management.
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The MME provides security functions such as providing temporary identities for user terminals, interacting with Home Subscriber Server (HSS) for authentication, and negotiation of ciphering and integrity protection algorithms.
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It is also responsible for selecting the appropriate serving and PDN gateways, and selecting legacy gateways for handovers to other GERAN or UTRAN networks.
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MME manages thousands of eNodeB elements, which is one of the key differences from 2G or 3G.
4. POLICY AND CHARGING RULES FUNCTION (PCRF) •
It is a concatenation of Policy Decision Function (PDF) and Charging Rules Function (CRF).
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The PCRF interfaces with the PDN gateway and supports service data flow detection, policy enforcement, and flowbased charging.
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MODULE 1 CHAPTER 2  WIRELESS FUNDAMENTALS 1.
CELLULAR SYSTEM Cellular system mainly comprised of 3 parameters: 1. The cellular concept 2. Sectoring 3. Analysis of cellular system
1.1 THE CELLULAR CONCEPT • AT&T proposed a core idea of cellular system in 1971. • In cellular systems, the service area is subdivided into smaller geographic areas called cells. • Each cell has a Base Station (BS)/Base Transceiver Station(BTS) with or without a Mobile Station(MS). • To prevent interference between cells, neighboring cells do not use same set of frequencies.
➢ Core cellular Principles •
The major transmitting stations between cells include Mobile Station (MS), Base Station (BS), Base Station Controller (BSC) and an Mobile station controller (MSC). CELL A
MS
BS BSC
CELL B
MS
BS MSC
CELL C
MS
BS
BSC
MSC
Figure 1: Simple cellular system architecture
➢ Frequency planning • The same frequencies used by cells in the different clusters can be reused and the process is called frequency reuse. • It is required to determine a proper frequency reuse factor and a geographic reuse pattern. • Frequencies can be reused, such that the interference between base stations is kept to an acceptable level. • The frequency reuse factor f is defined as f ≤ 1, Where f = 1 means that all cells reuse all the frequencies. f = 1/3 means frequency is reused by 1 cell out of every 3 cells in a cluster.
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Figure 2: Frequency reuse pattern
➢ Cocells and cluster • Cocells are cells in cellular system which uses the same frequency channel set. • The reuse of the same frequency channels should be intelligently planned in order to maximize the geographic distance between the cochannel base stations. • Figure 3 shows an example of hexagonal cellular system model with frequency reuse factor f = 1/7. • The groups of cells which are using entire frequency channels set are called “clusters”.
Figure 3: Standard figure of a hexagonal cellular system with f =1/7.
➢ Cellular system capacity • The overall system capacity can be increased by making the cells smaller and turning down the power. • As the cell size decreases, the transmit power of each base station also decreases correspondingly. • For example, if the radius of a cell is reduced by half when the propagation path loss exponent is 4, the transmit power level of a base station is reduced by 12 dB (=l0log16 dB).
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➢ Handoff • Since cellular systems support user mobility, call transfer from one cell to another should be provided. • The handoff process provides a transfer of a connection from one base station to another.
➢ Advantages of cellular concept • Small cells give a large capacity advantage and reduce power consumption and allow frequency reuse.
➢ Drawback of cellular system • As cell size decreases, the number of cells for the same service area needs more base stations and their associated hardware costs also increases. • It leads to frequent handoffs. • Interference level increases and effect on service efficiency.
1.2
SECTORING • Sectoring is a capacity expansion technique which is achieved by keeping the cell radius unchanged and is a method used to decrease the D /R (Distance/Radius) ratio. • It is a technique to improve SIR (Signal to Interference noise Ratio) without using much bandwidth. • Cochannel interference can be reduced by using directional antennas instead of Omnidirectional antenna at the base station. •
It provides interference reduction, hence S/I ratio increases.
• No capacity is lost from sectoring because each sector can reuse time and code slots, so each sector has the same nominal capacity as an entire cell. • In sectored cellular system, capacity in each sector is actually higher than that in a nonsectored cellular system because the interference is reduced by sectoring. •
An illustration of sectoring is shown in Figure 4.
Figure 4: Threesector (120degree) and Sixsector (60degree) cells Meghana M N, Assistant Professor, MITT
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• In Figure 4(a), if each sector 1 points the same direction in each cell, then the interference caused by neighboring cells will be dramatically reduced. • An alternative way to use sectors is to reuse frequencies in each sector and the time/code/frequency slots can be reused in each sector, but there is no reduction in the experienced interference. • As the number of sectors per cell increases the SIR also increases, thus the capacity of cellular system increases.
➢ Advantages of sectoring 1. It is an effective and practical approach to the OCI (Other Cell Interference) problem. 2. It is an antenna technique to increase the system capacity.
➢ Drawback 1. Sectoring increases the number of antennas at each base station, hence it increases the cost and the number of handoffs increases. 2. It reduces efficiency due to channel sectoring at the base station. 3. It also increases the overhead due to the increased number of inter sector handoffs. 4. It causes inter sector interference as well as power loss.
➢ New Approaches to other Cell Interference Following are other approaches to reduces cell interference 1. Use advanced signal processing techniques at the receiver and/or transmitter as a means of reducing or cancelling the perceived interference. 2. Use networklevel approaches such as cooperative scheduling or encoding across Base station. Adopt multicell power control and distributed antenna technique.
1.3 ANALYSIS OF CELLULAR SYSTEM •
The performance of wireless cellular systems is significantly limited by Cochannel interference (CCI) and other cell interference (OCI) which comes from other users in the same cell or from other cells.
•
The cellular systems performance (capacity, reliability) is measured by SIR of the desired cell, i.e., the amount of desired power to the amount of transmitted power.
•
The spatial isolation between cochannel cells can be measured by defining the parameter Z, called cochannel reuse ratio is given by 𝑍=
𝐷 3 = √ 𝑅 𝑓
Where, D = distance between the cocells R = radius of the desired cell Meghana M N, Assistant Professor, MITT
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1/f = size of the cluster and inverse of the frequency reuse factor N, i.e. 1/f = N 𝐷 = √3𝑁 𝑅 As the cluster size 1/f = N increases, CCI decreases, so that it improves the quality of communication link 𝑍=
•
and capacity. •
However, the overall spectral efficiency decreases with the size of a cluster, so f should be chosen just small enough to keep the received signaltointerferencenoise ratio (SINR) above acceptable levels.
➢ Signal to Noise ratio (SNR) of cellular system •
SNR of a cellular system is given by 𝑆 𝐼
=
𝑆
∑𝑁𝑙 𝑖=1 𝐼𝑖
Where S = Received power of desired signal and Ii = Interference power from the ith cocell base station •
The received SIR depends on the location of each mobile station, and it should be kept above an appropriate threshold for reliable communication.
•
The received SIR at the cell boundaries is of great interest since this corresponds to the worst interference scenario.
•
The received SIR for the worst case described in Figure 5 and its empirical path loss formula given as
𝑆 𝑥0 = 𝐼 𝑥0 + ∑2𝑖=1 𝑥𝑖 + 2−∝ ∑5𝑖=3 𝑥𝑖 + (2.633)−∝ ∑11 𝑖=6 𝑥𝑖
Where, xi = shadowing from the ith base station ∝ = path loss components
x o= lognormal distribution for the shadowing value
Figure 5: Forward link interference in a hexagonal cellular system (worst case)
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➢ Outage probability (P0 ) •
The outage probability is the received SIR falls below a threshold can be derived from the distribution.
• If the mean and standard deviation of the lognormal distribution are𝛼 and 𝜎 in dB, the outage probability is derived in the form of Q function is given by
𝑃 𝑜𝑢𝑡 = 𝑃[𝑆𝐼𝑅 < 𝛾 ] = 𝑄 (
•
𝛾−𝜇 𝜎
) Where 𝛾 = threshold SIR level in dB.
Lower frequency reuse factor is typically adopted in the system design to satisfy the target outage probability at the sacrifice of spectral efficiency.
2. BROADBAND WIRELESS CHANNEL (BWC) In wireless, broadband is the wide bandwidth data transmission which transports multiple signals.
2.1 PATH LOSS IN BROADBAND WIRELESS CHANNEL (BWC) ***** [4M] June/july 2019 •
Path loss is defined as the ratio of the transmit power to the receive power.
•
Path loss model relates the path loss between the transmitter and receiver.
•
Assuming an isotropic antenna is used as shown in figure 6, the propagated signal energy expands over a spherical wavefront, so that the energy received at the antenna with a distance of d away is inversely proportional to the sphere surface area 4πd2.
Figure 6: free space propagation
•
The free space path formula or FRIIS formula is given as
𝜆2 𝐺𝑡 𝐺𝑟 𝑃𝑟 = 𝑃𝑡 ( 4𝜋𝑑)2
Where Pr = received power, Pt = transmitted power and 𝜆 = wavelength.
And also we know that C = f cλ => λ = C/fc where C is the spped of light.
•
The average value of channel gain is given as
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Where E[.] denotes expected value or mathematical mean. •
If the directional antenna is used at the transmitter or receiver the gain Gt and/or Gr is achieved, and the received power is simply increased by the gain of these antennas.
•
Reflection from the earth and other objects will tend to increase the received power at the receiver, because of the reflected waves experience a 180 degree phase shift at relatively larger distance this reflection creates destructive interference.
•
Path loss for such destructive interference is given as
•
One of the simplest and most common is the empirical path loss formula given as
•
Path loss for such destructive interference is given as
𝐺𝑡 𝐺𝑟 ℎ 2𝑡 ℎ2𝑟 𝑃𝑟 = 𝑃𝑡 𝑑4 𝑑𝑜 ∝ 𝑃𝑟 = 𝑃𝑡 ( ) 𝑑
Where Po is a measured path loss at a distance do .
2.2 SHADOWING IN BROADBAND WIRELESS CHANNEL (BWC) ***** [4M] June/july 2019 •
In Path loss, distance was the major factor effect on the total received power. However many factors apart from distance can have a large effect on the total received power.
Figure 7: shadowing can cause large deviations from path loss predictions
•
For example, as shown in figure 7, obstacles such as trees and buildings may be located between the transmitter and receiver and cause temporary degradation in the received signal strength.
•
Shadowing is the effect that the received signal power fluctuates due to objects obstructing the propagation path between transmitter and receiver.
•
•
With shadowing the empirical path loss formula given as
𝑑𝑜 ∝ 𝑃𝑟 = 𝑃𝑡 𝑃𝑜 𝜒 ( ) 𝑑
Where 𝜒 = sample of the shadowing random process
Hence the received power is now modeled as a random process.
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MODULE 1
The distance trend in the path loss can be thought of as the mean received power.
•
The χ causes a deviation of a signal from the expected values. Typically it has a correlation distance of meters to tens of meters.
•
Hence shadowing is also called as Large scale fading.
•
The shadowing value is modeled as lognormal random variable that is 𝜒 = 10 𝑥 ⁄10 𝑤ℎ𝑒𝑟𝑒 𝑥 ∼ 𝑁 (0, 𝜎 𝑠2 )
Where 𝑁(0, 𝜎2𝑠 ) is an Gaussian distribution with a mean 0 and variance 𝜎𝑠2 and it’s typical value ranges from 612dB.
2.3 FADING IN BROADBAND WIRELESS CHANNEL (BWC) •
FADING: Fading in wireless channel is defined as attenuation of signal with various variables like time, location and frequency range and caused due to reception of multiple version of same signal.
•
The multiple received signals are caused by reflections that are referred to as multipath.
•
The multipath signals may arrive close to each other or at the same time to the receiver.
•
The multiple different paths between the transmitter and receiver are shown in Figure 8.
Figure 8: The channel may have a few major paths with quite different lengths, and then the receiver may see a number of locally scattered versions of those paths.
➢ Fading effect •
When some of the reflections arrive at nearly the same time, the combined effect of those reflections shown in Figure 9.
•
Depending on the phase difference between the arriving signals, the interference can be either constructive or destructive, which causes a very large observed difference in the amplitude of the received signal even over very short distances.
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Figure 9: The difference between constructive interference (top) and destructive interference (bottom) at 4 = 2.5GHz is less than 0.1 nanoseconds in phase, which corresponds to about 3 cm
•
The moving the transmitter or receiver for a very short distance can have a major effect on the received amplitude, even though the path loss and shadowing effects may not have changed at all.
➢ Timevarying tappeddelay line channel model of fading: •
If the transmitter or receiver move relative to each other, then the channel response h(t) will change.
•
This channel response can be thought of as having two dimensions as shown in Figure 10: I. Delay dimension (τ) II. Timedimension(t)
Figure 10: The delay τ corresponds to how long the channel impulse response lasts. The channel is time varying, so the channel impulse response is also a function of time, i.e., h (τ, t), and can be quite different at time (t + ∆t) than it was at time t.
•
Since the channel changes over distance (and hence time), the values of h 0, h 1,…,hv may be totally different at time t vs. time t + ∆t. Because the channel is highly variant in both the τ and t dimensions.
•
The fundamental function used to statistically describe broadband fading channels is the twodimensional autocorrelation function A(∆τ, ∆t).
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MODULE 1
The autocorrelation function is defined as A(Δτ, Δt) = E[h(τ 1,t1) h*( τ2,t2 )] = E[h(τ1,t) h *( τ 2,t+Δt)]
(step 1)
= E[h(τ,t) h * ( τ+Δτ,t+Δt)] (step 2) •
In step 1 assume channel response is Wide Sense Stationary (WSS), hence autocorrelation function depends on Δt where Δt = t2 – t 1.
•
In step 2 assume channel response of paths arriving at different times τ1 and τ2 are uncorrelated. Hence τ 1 and τ2 are replaced by τ = τ1  τ2.
•
Hence the above equation is referred to as Wide Sense Stationary Uncorrelated Scattering (WSSUS), which is the most popular model for wideband fading channels.
3. WIRELESS
CHANNEL
PARAMETERS
/
BROADBAND
FADING
PARAMETERS***** The key broadband fading parameters to evaluate the wireless channels are: 1. Delay Spread and Coherence Bandwidth 2. Doppler Spread and Coherence Time***** 3. Angular Spread and Coherence Distance***** Summary of broadband fading parameters with rule of thumb is shown in table 1.
Table 1: summary of broadband fading parameters with rules of thumb Meghana M N, Assistant Professor, MITT
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(https://en.wikipedia.org/wiki/Multipath_propagation) (https://en.wikipedia.org/wiki/Lineofsight_propagation) (https://en.wikipedia.org/wiki/Lineofsight_propagation) (https://en.wikipedia.org/wiki/Root_mean_square) WIRELESS CELLULAR & LTE 4G BROADBAND – 15EC81 MODULE 1
3.1 DELAY SPREAD AND COHERENCE BANDWIDTH ➢ Delay Spread •
The delay spread is mostly used in the characterization of wireless channels.
•
It is a measure of the multipath richness of a communications channel.
• •
It specifies the duration of the channel impulse response ℎ (𝜏, 𝑡).
The delay spread is the amount of time that elapses between the first arriving path (typically the lineofsight component) and the last arriving (nonnegligible) path.
•
The delay spread can be found by inspecting 𝐴 (∆𝜏, 0) by setting ∆𝑡 = 0 in the channel autocorrelation function. It is often referred to as the Multipath Intensity Profile, or power delay profile.
•
The maximum delay spread is 𝜏𝑚𝑎𝑥. Characterized wireless channel with number of delay taps v will be needed in the discrete representation of the channel impulse response, since v ≈
•
τ max Ts
Where Ts = Sampling time
Delay spread can be quantified through different metrics, although the most common one is the root mean square (rms) delay spread.
𝜏rms gives the measure of the width and spread of the channel response in time.
•
Larger 𝜏𝑟𝑚𝑠 implies a highly dispersive channel in time and a large impulse response ( v) and Smaller
•
A general rule of thumb is that 𝜏𝑚𝑎𝑥 = 5 𝜏𝑟𝑚𝑠.
𝜏𝑟𝑚𝑠 implies that the channel is not very dispersive.
➢ Coherence Bandwidth ( Bc) • • •
It is a statistical measurement of the range of frequencies over which the channel can be considered "flat".
The Bc is the frequency domain dual of the channel delay spread.
The coherence bandwidth gives a rough measure for the maximum separation between a frequency f1 and a frequency f2 where the channel frequency response is correlated. That is f1 − f 2 ≤ BC ⇒ H (f1 ) ≈ H(f 2 )
•
f 1 − f 2  > BC ⇒ H(f1) & H(f2 ) are uncorrelated.
𝜏𝑚𝑎𝑥 is a value describing the channel duration, 𝐵𝑐 is a value describing the range of frequencies over which the channel stays constant. Given the channel delay spread, it can be shown that BC ≈
•
1 1 ≈ 5τrms τmax
The important and prevailing feature is that 𝐵𝑐 and 𝜏𝑟𝑚𝑠 are inversely related.
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3.2 DOPPLER SPREAD AND COHERENCE TIME***** [4M] June/July 2019 •
Doppler spread and coherence time are parameters which describe the time varying nature of the channel in a smallscale region.
➢ Doppler Spread(B D ) •
Doppler spread is a measure of the spectral broadening caused by the rate of change of the mobile radio channel.
•
It is defined as the range of frequencies over which the received Doppler spectrum is nonzero.
•
The Doppler power spectrum is plotted with statistical power distribution of the channel versus frequency for a signal transmitted at just one exact frequency.
•
The power delay profile is caused by multipath between the transmitter and receiver.
•
The Doppler power spectrum is caused by motion between the transmitter and receiver.
•
The Doppler power spectrum is the Fourier transform of At(∆t) is given by ∞
ρt = ∫ At (∆t)e −∆f.∆t(d∆t) •
−∞
When a pure sinusoidal tone of frequency fc is transmitted, the received signal spectrum, called the Doppler spectrum.
• •
The spectrum ranges from 𝑓𝑐 – 𝑓𝑑 𝑡𝑜 𝑓𝑐 + 𝑓𝑑, where fd is the Doppler shift.
The amount of spectral broadening depends on fd and the maximum Doppler spread fd is given by fd =
vfc c
Where v = maximum speed between the transmitter and receiver, fc = the carrier frequency and c = the speed of light.
• •
Until the bandwidth 𝐵 tC ⇒ h(t 1) & h( t 2) are uncorrelated .
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•
The coherence time and Doppler spread are also inversely related
•
Values for the Doppler spread and the associated channel coherence time for LTE at Pedestrian, Vehicular,
1 Tc ≈ fd
and Maximum Speeds are given in Table 2 for two possible LTE frequency bands.
Table 2: Doppler spread and approximates coherence times for LTE at pedestrian, vehicular and maximum speeds
•
At high frequency and mobility, the channel may change up to 1000 times per second, it results in a large overhead on channel and Channel estimation algorithms.
3.3 ANGULAR SPREAD AND COHERANCE DISTANCE***** [4M] June/July 2019 •
Angular Spread and Coherence Distance give the measure of how far the antennas have to the placed and the antenna angle for signal transmission.
•
Angular spread and coherence distance are particularly important in multiple antenna (MIMO) systems.
➢ Angular Spread (θrms) • •
It refers to the measure of the angle of the arriving energy.
A large 𝜃 𝑟𝑚𝑠 implies that channel energy is coming in from many directions and a small 𝜃𝑟𝑚𝑠 implies that the channel energy is coming in from only one direction.
•
A large angular spread generally occurs when there is a lot of local scattering.
➢ Coherence Distance (D C) •
The coherence distance is the measure of distance between the antenna’s in the region.
•
The coherence distance is the spatial distance over which the channel does not change.
•
The dual of angular spread is coherence distance.
•
As the angular spread increases, the coherence distance decreases, and vice versa.
•
If the coherence distance is very small, antenna arrays will provide rich diversity.
•
An approximate rule of thumb between angular spread and coherence distance is 𝐷𝐶 ≈
Meghana M N, Assistant Professor, MITT
2𝜆 𝜃𝑟𝑚𝑠
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(https://en.wikipedia.org/wiki/Scattering) WIRELESS CELLULAR & LTE 4G BROADBAND – 15EC81
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4. MODELING BROADBAND FADING CHANNELS •
Modeling a channel specifies calculating all the physical processing effecting of signal from the transmitter to the receiver.
•
The two major classes of models are: 1. Statistical models 2. Empirical models
4.1 STATISTICAL MODELS •
Statistical models are simpler and are useful for analysis and simulations using mathematical approach.
•
These models are used to characterize the amplitude and power of a received signal r(t) when all the reflections arrive at about the same time.
•
This is only true when the symbol time is much greater than the delay spread, i.e., T >>𝜏𝑚𝑎𝑥 so these models are often said to be valid for "narrowband fading channels.
•
Some of the popular statistical models are: 1. Rayleigh Fading 2. Ricean Distribution 3. Nakagamim fading
1. RAYLEIGH FADING •
Rayleigh fading is a model that is used to describe the form of fading that occurs when multipath propagation exists.
•
Rayleigh fading is used when there is many objects in the environment that scatter the radio signal before it arrives at the receiver.
•
The received signal component can be classified as inphase r I(t) and quadrature rQ(t) components of r(t) of a Gaussian random variables.
•
Consider a snapshot of a received signal r(t) at time t = 0, and r(0) = rI(0) + rQ (0).
• The distribution of the envelope amplitude is given as 𝑟 = √𝑟𝐼2 + 𝑟𝑄2 and the received power is given as
• Rayleigh fading equation is given as
Meghana M N, Assistant Professor, MITT
𝑟 2 = 𝑟I2 + 𝑟𝑄2 2𝑥 −𝑥 𝑓𝑟 (𝑥) = 𝑒 𝑃𝑟 , 𝑥 ≥ 0 𝑃𝑟 2
25
(http://www.wirelesscommunication.nl/reference/chaptr03/ricepdf/rice.htm)
WIRELESS CELLULAR & LTE 4G BROADBAND – 15EC81
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1 𝑃𝑟 𝑓 (𝑥) = 𝑃𝑟 𝑒 , 𝑥 ≥ 0 Where Pr is the average received power due to shadowing and path loss. 2
𝑟 
• Gaussian random variables r I(t) and r Q (t) each have zero mean and variance 𝜎2 = • The phase of r(t) uniformly distributed from 0 to 2π is defined as 𝑟𝑄 𝜃𝑟 = 𝑡𝑎𝑛 −1 ( ) 𝑟𝐼
𝑃𝑟 2
.
• The path loss and shadowing determine the mean received power and the total received power fluctuates around this mean due to the fading. This is demonstrated in Figure11.
Figure 11: The three major channel attenuation factors are shown in terms of their relative spatial (and hence temporal) scales.
2. RICEAN DISTRIBUTION (LINE OF SIGHT CHANNELS) • An important assumption in the Rayleigh fading model is that all the arriving reflections have a mean of zero. • In Ricean fading, a strong dominant component is present for example, a lineofsight (LOS) path between the transmitter and receiver. • For a LOS signal, the received envelope distribution is modelled by a Ricean distribution, which is given by 𝑓𝑥 (𝑥 ) =
2) 𝑥 −(𝑥2 +𝜇 𝑥𝜇 2 2𝜎 𝐼 ( 𝑒 ),𝑥 ≥ 0 0 𝜎2 𝜎2
Where 𝜎 = standard deviation, µ = mean which determines power of LOS and x = value set.
• Ricean distribution reduces to the Rayleigh distribution in the absence of a LOS component i.e. by 𝑥𝜇
equating µ = 0 => 𝐼0 (𝜎 2 ) = 1.
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• Since the Ricean distribution depends on the LOS component's power µ 2, a common way to characterize the channel is by the relative strengths of the LOS and scattered paths. • The LOS factor K is quantified as
µ2 𝐾= 2𝜎
• K=0 specified single LOS the ricean distribution reduces to Rayleigh and K=∞ specifies multiple LOS. • The average received power in ricean fading is the combination of the scattering power and the LOS power given as
𝑃𝑟 = 2𝜎 2 + 𝜇 2
3. NAKAGAMIm FADING (THE GENERAL MODEL) •
It is a general model for wireless channel. The probability density function (PDF) of Nakagami fading is parameterized by m and given as
2𝑚 𝑚 𝑥 2𝑚−1 −𝑚𝑥 𝑓𝑟 (𝑥 ) = 𝑒 𝑃𝑟 , 𝑚 ≥ 0.5 Γ(𝑚)𝑃𝑟𝑚
Where m = shape parameter gives as 𝑚 =
2
(𝐾+1) 2
(2𝐾+1)
•
If m=0 gives Rayleigh equation and if m=∞ then the received power Pr tends to be constant.
•
Nakagamim fading is given as
•
Figure 12 shows comparison of the most popular fading distributions with probability distributions f r(x)
𝑚 𝑚 𝑥𝑚−1 −𝑚𝑥 𝑓𝑟 2 ( 𝑥) = ( ) 𝑒 𝑃𝑟 , 𝑚 ≥ 0.5 𝑃𝑟 Γ(𝑚)
for Rayleigh, Ricean w/K = 1, and Nakagami with m =2. All have average received power Pr =1.
Figure 12: probability distribution for Rayleigh, ricean and nakagami
4.2 EMPIRICAL CHANNEL MODELS •
Statistical channel models do not take into consideration of specific wireless propagation environments.
•
Modeling of a channel requires the complete knowledge of the surrounding (ex. Buildings, plants, etc.), time and computational demand. Hence empirical and semi empirical models were developed.
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MODULE 1
Empirical and semiempirical wireless channel models are the specific models, which have been developed to accurately estimate the path loss, shadowing, and smallscale fast fading.
•
Empirical model are created by observation and experiment rather than mathematical aspects.
•
These are more complicated but usually represent a specific type of channel more accurately.
•
These models considers the realistic factors such as Angle of Arrival (AoA), Angle of Departure (AoD), Antenna Array Fashion (AAF), Angle Spread (AS), and Antenna Array Gain(AAG) pattern and other real time factors.
•
Different empirical channel models exist for different wireless scenarios, such as sub urban macro, urban macro, urban micro cells, and so on.
1. LTE CHANNEL MODELS FOR PATH LOSS •
These models are widely used in modeling the outdoor macro and micro cell wireless environments.
•
These are also referred to as "3GPP" channel models.
•
It provides a measure of Base Station (BS) to Base Station(BS) distance.
•
First step is to specify the environment here an empirical channel model is used, e.g., suburban macro, urban macro, or urban micro environment.
•
The BS to BS distance is typically larger tan 3 km for a macrocell environment and less than 1 km for an urban microcell environment.
•
For macrocell environment, the path loss is given by COST HATA MODEL, which is given as
𝑃𝐿𝐶 [𝑑𝐵 ] = (44.9 − 6.55𝑙𝑜𝑔10 (ℎ𝑏) )𝑙𝑜𝑔10 (𝑑) + 46.3 + 33.9𝑙𝑜𝑔10 (𝑓𝑐 ) − 13.82𝑙𝑜𝑔10 (ℎ𝑏 ) − 𝑎 (ℎ𝑚 ) + 𝐶0
Where h𝑏= Base station antenna height
fc= Carrier frequency in MHz d = Distance between the BS and MS in kilometer C 0 = COST HATA model constant a(hm) = relatively negligible correction function for the mobile height defined as
a(ℎ𝑚) = (1.1𝑙𝑜𝑔 10(𝑓𝑐) − 0.7) ℎ 𝑚 − 1.56𝑙𝑜𝑔10(𝑓𝑐) − 0.8 • •
wh𝑒𝑟𝑒 h𝑚 = mobile antenna height.
COST Hata model is considered to be accurate when d = 100m to 20 km and 𝑓𝑐 = 1500 to 2000MHz.
LTE system also operates with below 1500Mhz, for example 700MHz, the empirical channel model used in such scenarios is the HATA MODEL.
•
HATA model is closely related to the COST Hata model, but with slightly different parameters.
•
HATA models exist depending on whether the environment is urban, suburban, or for open areas.
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MODULE 1
HATA Model for Urban areas is given as
𝑃𝐿 𝐶[𝑑𝐵] = (44.9 − 6.55𝑙𝑜𝑔10 (ℎ𝑏 ))𝑙𝑜𝑔10 (𝑑) + 69.55 + 26.16𝑙𝑜𝑔10 (𝑓𝑐 ) − 13.82𝑙𝑜𝑔10 (ℎ𝑏 ) + 𝐶1 Where 𝐶1 = correction factor that varies depending on the size of the city. For medium and small city C1 is 𝐶1 = 0.8 + (1.1𝑙𝑜𝑔10 (𝑓𝑐 ) − 0.7)ℎ𝑚 − 1.56𝑙𝑜𝑔10 (𝑓𝑐 )
•
HATA Model for Sub Urban areas is given as
•
HATA Model for open areas is given as
2
𝑓𝑐 𝑃𝐿𝑆 [ 𝑑𝐵] = 𝑃𝐿 𝑈 − 2 (( 𝑙𝑜𝑔10 )) − 5.4 28
𝑃𝐿𝑜 [𝑑𝐵 ] = 𝑃𝐿 𝑢 − 4.78(𝑙𝑜𝑔10𝑓𝑐 )2 + 18.33𝑙𝑜𝑔 10(𝑓 𝑐) − 40.94
2. LTE CHANNEL MODELS FOR MULTIPATH •
The received signal at the mobile receiver consists of N timedelayed versions of the transmitted signal. Example as shown in figure 13.
Figure 13: 3GPP channel model for MIMO simulations
•
The N paths are characterized by powers and delays that are chosen according to prescribed channel generation procedures, as follows I.
The number of paths N ranges from 1 to 20 and is dependent on the specific channel models. For example, the 3GPP channel model has N = 6 multipath components.
II.
Each multipath component further corresponds to a cluster of M subpaths, where each subpath characterizes the incoming signal from a scatter.
•
III.
The M subpaths have random phases and subpath gains.
IV.
For 3GPP, the phases are random variables uniformly distributed from 0 to 360 degrees.
In the 3GPP channel model, the nth multipath component from the u th transmit antenna to the sth receive antenna, is given as
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3. LTE SEMIEMPIRICAL CHANNEL MODELS •
Constructing a fully empirical channel model is timeconsuming and computationally expensive due to the huge number of parameters involved.
•
Therefore semiempirical channel models are used which includes practical parameters in a real wireless system and maintaining the simplicity of statistical channel models.
•
Wellknown examples of the simpler multipath channel models include the 3GPP2 Pedestrian A, Pedestrian B, Vehicular A, and Vehicular B models, suited for lowmobility pedestrian mobile users and higher mobility vehicular mobile users.
•
The power delay profile of the channel is determined by the number of multipath taps and the power and delay of each multipath component.
•
Each multipath component is modeled as independent Rayleigh fading with a different power level, and
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the correlation in the time domain is created according to a Doppler spectrum. •
The Pedestrian A is a flat fading model corresponding to a single Rayleigh fading component with a speed of 3 km/hr.
•
Pedestrian B model corresponds to a power delay profile with four paths of delays [0, 0.11, 0.19, 0.41] µ s and the power profile given as [1, 0.1071, 0.0120, 0.0052] at 3 km/hr.
•
Vehicular A model, the mobile speed is specified at 30 km/hr. Four multipath components exist, each with delay profile [0, 0.11, 0.19, 0.41] µs and power profile [1, 0.1071, 0.0120, 0.0052].
•
For the vehicular B model, the mobile speed is 30km/h, with six multipath components, delay profile [0, 0.2, 0.8, 1.2, 2.3, 3.7] µs and power profile [1, 0.813, 0.324 0.158, 0.166, 0.004]. These models are often referred to as Ped A/B and Veh A/B.
•
LTE standard additionally defined extended delay profile with increased multipath resolution known as Extended Pedestrian A, Extended Vehicular A, and Extended Typical Urban. These profiles are given in Tables 2.4, 2.5, and 2.6.
5. STATISTICAL CORRELATION OF THE RECEIVED SIGNAL •
Specific statistical models like Rayleigh, Ricean, and Nakagamim provided the probability density functions (PDFs) that gave the likelihoods of the received signal envelope and power at a given time instant.
•
Use these PDF functions with the channel autocorrelation function, 𝐴𝑐(∆𝜏, ∆𝑡) in order to understand how the envelope signal r(t) evolves over time, or changes from one frequency or location to another.
•
Analysis of statistical correlation of received signal in different domains are 1. Time correlation 2. Frequency correlation 3. The Dispersion selectivity duality 4. Multidimensional correlation
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1. TIME CORRELATION • •
In the time domain, the channel ℎ (𝜏 = 0, 𝑡) get one new sample from a Rayleigh distribution for every Tc sec & interpolated with the autocorrelation function of 𝐴𝑡(∆𝑡). The autocorrelation function 𝐴𝑡(∆𝑡) describes how the channel is correlated in time as shown in figure 14.
•
Its frequency domain Doppler power spectrum 𝜌𝑡(∆𝑓 ) provides a bandlimited description of the same correlation. Since it is simply the Fourier transform of 𝐴𝑡 (∆𝑡).
Figure 14: Autocorrelation of the signal envelope in time, Ac(∆𝑡) which here is normalized by the Doppler fD.
For example, from this figure it can be seen that for ∆𝑡 = to 0.4/fD, which means that after 0.4/fD seconds, the fading value is uncorrelated with the value at time 0.
•
For the specific case of uniform scattering, Doppler power spectrum can be described as
•
A plot of this realization of 𝜌𝑡(∆𝑓 ) is shown in Figure 15. Which is often used to model the time
autocorrelation function 𝐴𝑐 (𝛿𝑡 ), and hence predict the time correlation properties of narrowband
fading signals.
Figure 15: The spectral correlation due to Doppler, 𝜌𝑡(∆𝑓 ) for uniform scattering
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2. FREQUENCY CORRELATION •
Fading in frequency is that the channel in the frequency domain, 𝐻(𝑓, 𝑡 = 0), can be thought of as consisting of approximately one new random sample every Bc Hz, with the values in between interpolated.
•
The correlated Rayleigh frequency envelope 𝐻 (𝑓) shown in Figure 16.
Figure 16: The shape of the Doppler power spectrum 𝝆𝒕(∆𝒇), determines the correlation envelope of the channel in time (top). Similarly, the shape of the Multipath Intensity Profile
•
The correlation function that maps from uncorrelated time domain (𝜏 domain) random variables to a
•
𝜌𝑡(∆𝑓) describes the channel time correlation in the frequency domain.
• •
correlated frequency response is the Multipath Intensity Profile, 𝐴𝜏(∆𝜏).
𝐴𝜏(∆𝜏), describes the channel frequency correlation in the time domain.
The values of H(f) are correlated over all frequencies are refer to as "flat fading," i.e., 𝜏𝑚𝑎𝑥 ≪ 𝑇 ).
3. THE DISPERSION SELECTIVITY DUALITY •
Selectivity and dispersion are two quite different effects from fading.
•
Selectivity means that the signal's received value is changed by the channel over time or frequency.
•
Dispersion means that the channel is spread out over time or frequency.
•
Selectivity and dispersion are timefrequency duals of each other. This is illustrated in Figure 17.
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Figure 17: The dispersionselectivity duality: Dispersion in time causes frequency selectivity, while dispersion in frequency causes time selectivity
4. MULTIDIMENSIONAL CORRELATION •
In reality, signals are correlated in time, frequency, and spatial domains.
•
A broadband wireless data system with mobility and multiple antennas is an example of a system where all three types of fading will play a significant role.
•
The concept of doubly selective (in time and frequency) fading channels has received recent attention for OFDM.
•
Highly frequencyselective channel as in a wide area wireless broadband network requires a large number of closely spaced subcarriers to effectively combat the ISI and small coherence bandwidth.
•
On the other hand, a highly mobile channel with a large Doppler causes the channel to fluctuate over the resulting long symbol period, which degrades the subcarrier orthogonally.
•
In the frequency domain, the Doppler frequency shift can cause significant ISI as the carriers become more closely spaced.
•
The mobility and multipath delay spread must reach fairly severe levels before this doubly selective effect becomes significant.
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6. MITIGATION OF NARROW BAND FADING ***** In wireless communication, narrow band refers to signals over a narrow range of frequencies.
6.1 THE EFFECTS OF UNMITIGATED FADING • The probability of bit error rate (BER) is the principle metric of interest for the physical layer of a communication system. • For a QAMbased modulation system, the BER in an additive white Gaussian noise (AWGN, no fading) can accurately be approximated by the following relation
•
𝑃𝑏 ≤
−1.5𝑆𝑁𝑅 0.2𝑒 (𝑀−1)
If M ≥ 4 is the MQAM, the probability of error decreases very rapidly (exponentially) with the SNR. Since the channel is constant, the BER is constant over time.
•
In a fading channel, the BER become a random variable that depends on the instantaneous channel strength and M level modulation, it given as
•
̅̅̅ 𝑃𝑏 ∝
𝑀 𝑆𝑁𝑅
For fading channel, BER goes down very slowly with SNR, only inversely. This trend is captured plainly in Figure 18 .
Figure 18: Flat fading causes a loss of at least 2030 dB at reasonable BER values.
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6.2 TECHNIQUES FOR MITIGATION OF NARROWBAND FADING There are 5 main techniques for migration of narrowband fading. 1. Spatial Diversity 2. Coding and Interleaving 3. Automatic Repeat Request ( ARQ) 4. Adaptive Modulation and Coding (AMC) 5. Combining Narrowband Diversity Techniques
1. SPATIAL DIVERSITY •
Diversity is the technique to overcome the fading problems in wireless channels by improving PER (Packet Error Rate) and BER (Bit Error Rate).
•
It is also known as antenna diversity and it usually is achieved by having two or more antennas at the receiver and/or the transmitter as shown in figure .
•
Spatial diversity is a powerful form of diversity, and desirable since it does not require redundancy in time or frequency.
•
The simplest form of space diversity consists of two receive antennas, where the stronger of the two signals is selected.
•
As long as the antennas are spaced sufficiently, the two received signals will undergo approximately uncorrelated fading.
•
This type of diversity is called selection diversity shown in figure 19.
•
More sophisticated forms of spatial diversity include receive antenna arrays (two or more antennas) with maximal ratio combining, transmit diversity using spacetime codes, transmit precoding, and other combinations of transmit and receive diversity.
•
Spatial signaling techniques are important in LTE techinques.
Figure 19: Simple twobranch selection diversity eliminates most deep fades.
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2. CODING AND INTERLEAVING •
Coding and interleaving is a form of diversity which is used everywhere for all wireless communication systems.
•
It is a form of time diversity, where in a multicarrier system they also can capture frequency diversity.
I. CODING •
Coding can be used in Error Correction Codes (ECCs), which is also known as Forward Error Correction (FEC).
•
ECCs introduce redundancy at the transmitter to allow the receiver to recover the input signal even if the received signal is significantly degraded by attenuation, interference, and noise.
•
Coding techniques can be categorized by their coding rate(r) which is the ratio of information bits to a coding process to the total number of bits created by the coding process.
•
The coding rate r ≤ 1, which is the inverse of the redundancy added.
•
A coding rate is ¼ indicates for each information bit into the coding process there will be 4 bits created for transmission.
•
The higher the code rate, the higher percentage of error detection/correction overhead.
•
Higher the coding rate gives higher transmission reliability gain.
•
There are 2 main different coding techniques: Convolution codes & turbo codes.
i.
CONVOLUTION CODES • Convolution encoder Convert any length message to a single codeword. •
Encoder has memory and has dK outputs that at any time depend on CK inputs and m previous input blocks.
•
In Figure 20 shows convolutional encoder defined by LTE for use in the Broadcast Channel (BCH).
Figure 20: The rate r = 1/3 convolutional encoder de fined by LTE for use in the Broadcast Channel (BCH)
• The above figures shows the rates of 1/3 code since there is one input bit (𝐶𝑘) and 3 outputs(𝑑𝑘). • The constraint length of this code is 7, there are 6 delay elements or 64 possible states.
• The generator polynomial G which consist of the generators G i for each 3 outputs in octal notation. • For example G 0 = 133 in binary form is 1011011, where a 0 means the output does not include this tap and a 1 means it does.
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TURBO CODES • It class of highperformance Forward Error Correction (FEC) codes. It is built using two identical convolutional codes of special type, such as, Recursive Systematic (RSC) type with parallel concatenation. • Turbo code provides flexibility and has an ability to recover quickly from errors through iterative decoding. • A rate turbo code is also deployed by LTE as shown in Figure 21.
Figure 21: The rate parallel concatenated turbo encoder defined by LTE for use in the uplink and downlink shared channels, among others.
• Turbo code comprises of 8state rate (4 states in each convolution encoder), 1 systematic encoder that operates on an interleaved input sequence, for a net coding rate of 1/3 . • By systematic, we mean that one output is generated by a linear modulo2 sum of the current encoder state that is a function of both the input bit(s) and the previous states (i.e., there is feedback in the state machine), while the other outputs are simply passed through to the output, like Xk in Figure . • Codes in LTE can also be punctured, which means that some of the output coded bits are simply dropped, in order to lower the transmission rate. • For example, if the output of a rate ½ and a convolutional code had a puncturing factor of 1/4 , this means that out of every four output bits, one is dropped. • Hence, the effective code rate would become 2/3, since only three coded bits are transmitted for every two information bits. • At the decoder, a random or fixed coded his is inserted in the decoding process.
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(https://en.wikipedia.org/wiki/Forward_error_correction#Interleaving)
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INTERLEAVING
• Interleaving is a process or methodology to make a system more efficient, fast and reliable by arranging data in a noncontiguous (random) manner. • Interleaving, a technique for making forward error correction more robust with respect to burst errors. • Interleaving is typically used in both convolutional coding and turbo coding. • For use with a conventional convolutional code, the interleaver shuffles coded bits to provide robustness to burst errors that can be caused by either noise and interference. • For both convolutional codes and turbo codes, the interleaver block size is quite large. • The interleaver block size is usually used over a single packet data or often much less than that. • Deinterleaving delays have been one of the primary drawbacks to turbocoding since they cause considerable latency. • Interleaving has proven very effective in allowing ECCs designed for constant, timeinvariant additive noise channels to also work well on fading, time variant noisy channels.
3. AUTOMATIC REPEAT REQUEST (ARQ) •
LTE uses ARQ (Automatic Repeat Request) and HybridARQ (HARQ) technique for flow and error control.
•
ARQ is used in MAC layer retransmission protocol that allows large packets to be quickly retransmitted.
•
These protocol works with physical layer ECCs and parity checks to ensure reliable links in channels.
•
Since a single bit error causes an error in the entire packet, with ARQ the entire packet must be retransmitted even when nearly all of the bits already received were correct, which is clearly inefficient.
•
HybridARQ combines the two concepts of ARQ and FEC (Forward Error Correction) to avoid such waste, by combining received packets.
•
HybridARQ is able to extract additional time diversity in a fading channel as well.
•
In HARQ a channel encoder such as a convolution encoder or turbo encoder is used to generate additional redundancy to the information bits.
•
Instead of transmitting all the encoded bits (systematic bits + redundancy bits), only a fraction of the encoded bits are transmitted.
•
This is achieved by puncturing some of the encoded bits to create an effective code rate greater than the native code rate of the encoder.
•
After transmitting the encoded and punctured bits, the transmitter waits for an acknowledgment from the receiver telling it whether the receiver was able to successfully decode the information bits from
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the transmission. •
If the receiver was able to decode the information bits, then nothing else needs to be done. If, on the other hand, the receiver was unable to decode the information bits, then the transmitter can resend another copy of the encoded bits.
4. ADAPTIVE MODULATION AND CODING (AMC) ***** [7M] June/july 2019 •
LTE systems employ Adaptive Modulation and Coding (AMC) in order to reduce fluctuations in the channel over time and frequency.
•
The basic idea of AMC: ➢
Transmit at a high data rate when the channel is good.
➢
Transmit at a lower rate when the channel is poor in order to avoid excessive dropped packets.
➢
Lower data rates are achieved by using a small constellation such as QPSK and low rate error correcting codes such as rate 1/3 turbo codes.
➢
The higher data rates are achieved with large constellations such as 64QAM and less robust error correcting codes.
•
To perform AMC, the transmitter must have some knowledge of the instantaneous channel gain.
•
Once it does, it can choose the modulation technique that will achieve the highest possible data rate while still meeting a BER or PER (Packet Error Rate) requirement.
•
An alternative way to achieve high data rate is to maximize the throughput.
•
A block diagram of an AMC system is given in Figure 22. For simplicity, consider just a single user system attempting to transmit as quickly as possible through a channel with a variable SINR, for example, due to fading.
Figure 22: Adaptive modulation and coding block diagram
•
The goal of the transmitter is to transmit data from its queue as rapidly as possible, subject to the data being demodulated and decoded reliably at the receiver.
•
Feedback is critical for adaptive modulation and coding since the transmitter needs to know the "channel SINR".
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A Practical Example of AMC: Figure 23 shows a possible realization of AMC, using three different code rates (1/2, 2/3, 3/4), and three different modulation types (QPSK, 16QAM, 64QAM).
Figure 23 : Throughput vs. SINR, assuming the best available constellation and coding configuration is chosen for each SINR
•
Throughput increases as SINR increases.
•
In this example lower offered data rate is QPSK and rate ½ turbo codes, while the highest data rate is 64QAM and rate ¾ turbo codes.
•
The achieved throughput normalized by the bandwidth is given as Where PER = Packet Error Rate
𝑇 = (1 − 𝑃𝐸𝑅 )𝑟 𝑙𝑜𝑔2(𝑀) 𝑏𝑝𝑠/𝐻𝑧
r = coding rate, r ≤ 1 and M = number of points in the constellation
5. COMBINING NARROWBAND DIVERSITY TECHNIQUES •
Combination of various narrowband techniques can maximize gain and robustness in the channel.
•
Use of diversity in one domain can decrease the gain in another domain; hence combination with other technique can increase the gain as well as robustness.
7. MITIGATION OF NARROW BAND FADING ***** •
In LTE Inter Symbol Interference (ISI) is the serious problem. This is due to frequency selective fading which causes dispersion in time.
•
OFDM is the most popular choice for combating ISI in a range of high rate systems.
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Other main techniques for ISI mitigation of narrow band fading are: 1.
Spread Spectrum and RAKE Receivers
2.
Equalization
3.
Multicarrier Modulation: OFDM
4.
SingleCarrier Modulation with Frequency Domain Equalization
1. SPREAD SPECTRUM AND RAKE RECEIVERS •
It is a technique of transmitting of narrowband data signal in a wideband channel called spread spectrum.
•
RAKE receiver is used to counter the effect of multipath fading.
•
Spread spectrum techniques are generally broken into two different categories: 1. Direct Sequence Spread Spectrum(DSSS): It also known as Code Division Multiple Access (CDMA), is used widely in cellular voice networks and is effective at multiplexing a large number of variable rate users in a cellular environment. 2. Frequency hopping Spread Spectrum (FHSS): Frequency hopping is used in lowrate wireless LANs like Bluetooth, and also for its interference averaging properties in GSM cellular networks.
•
Spread spectrum techniques is not an appropriate technology for high data rates due selfinterference. In short, spread spectrum is not a natural choice for wireless broadband networks.
•
Although this selfinterference can be corrected with an equalizer this largely defeats the purpose of using spread spectrum to help with ISI.
2. EQUALIZATION •
Equalizers are a technique which is used to suppress ISI without the use of additional bandwidth or antennas.
•
Equalizers are implemented at the receiver, and attempt to reverse the distortion introduced by the channel.
•
Equalizers are broken into two classes: linear and decisiondirected (nonlinear).
1. Linear Equalizers: •
In linear equalizer, the received signal is passed through a digital filter which generally uses FIR filer.
•
The problem with this approach is that it inverts not only the channel, but also the received noise.
•
This noise enhancement can severely degrade the receiver performance, especially in a wireless channel with deep frequency fades.
•
Linear receivers are relatively simple to implement, but achieve poor performance in a t imevarying and severeISI channel.
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2. Nonlinear Equalizers: •
A nonlinear equalizer uses previous symbol decisions made by the receiver to cancel out their subsequent interference, and so is often called a Decision Feedback Equalizers (DFE).
•
Problem with this approach is that it is common to make mistakes about what the prior symbols were (especially at low SNR), which causes error propagation and is a time consuming approach due to feedback.
•
Nonlinear equalizers increase the computational complexity.
3. MULTICARRIER MODULATION: OFDM •
Multicarrier modulation is used to fight against the timedispersive ISI channel.
•
For a large number of subcarriers (L) are used in parallel, so that the symbol time for each goes from T to LT.
•
In Multicarrier system, rather than sending a single signal with data rate R and bandwidth B, L signals at the same time can be sent, each having bandwidth B/L and data rate R/L.
•
If B/L ≪ Bc, each of the signals will undergo approximately flat fading and the time dispersion for each signal will be negligible.
•
As long as the number of subcarriers L is large enough, the condition B/L ≪ Bc, can be met.
4. SINGLECARRIER
MODULATION
WITH
FREQUENCY
DOMAIN
EQUALIZATION (FDE) •
A primary drawback of the OFDM approach has a high PeaktoAverage Ratio (PAR).
•
The dynamic range of the transmit power is too large, which results in either significant clipping or distortion, or in a requirement for highly linear power amplifier.
•
One can transmit a single carrier signal with a cyclic prefix, which has a low PAR and then do all the processing at the receiver.
•
FDE uses Fast Fourier Transform (FFT) to move the signal into the frequency domain, a 1tap frequency equalizer (just like in OFDM), and then an Inverse FFT (IFFT) to convert back to the time domain for decoding and detection.
•
In addition to eliminating OFDM's PAR problem, an additional advantage of this approach for the uplink is the potential to move the FFT and IFFT operations to the base station.
•
In LTE multiple uplink users share the frequency channel at the same time, the mobile station still must perform FFT and IFFT operations.
•
In LTE resulting approach is known as SingleCarrier Frequency Division Multiple Access(SCFDMA).
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