Principles of Mobile Communication

This chapter begins with a brief history of wireless systems and standards, including cellular land mobile radio systems, cordless telephone systems, and wireless local and personal area networks (LANs and PANs). The discussion of cellular standards includes first generation (1G) analog cellular, second generation (2G) GSM, IS-54/136, IS-95, PDC, third generation (3G) cdma2000, UMTS, fourth generation (4G) WiMAX, LTE/LTE-A/LTE-A Pro, and an outlook on fifth generation (5G) cellular and beyond. The discussion of cordless phone standards includes DECT and PHS, and the discussion of local and personal area networks includes IEEE802.11, IEEE802.15, and Bluetooth. The chapter then introduces the rest of the textbook, starting with frequency reuse and the cellular concept. It goes on to discuss the main propagation phenomenon that are found in cellular land mobile radio environments, including additive channel impairments such as co-channel interference and noise. Afterwards, the cellular land mobile radio link budget is considered, including the effects of interference loading, shadow margin, and handoff gain that are peculiar to cellular land mobile radio systems. The chapter concludes with a discussion of coverage and capacity issues for cellular land mobile radio systems.

The design of spectrally efficient wireless communication systems requires a thorough understanding of the radio propagation channel. This chapter emphasizes land mobile radio channels, including those found in cellular land mobile radio systems and mobile ad hoc networks including vehicle-to-vehicle channels. The chapter first treats the characteristics of the complex faded envelope in frequency non-selective (flat) fixed-to-mobile channels that are typically found in cellular land mobile radio systems, including the received envelope and phase distribution, envelope correlation and spectra, level crossing rates and fade durations, and space-time correlation. Afterwards, mobile-to-mobile channels are considered. This is followed by a statistical characterization of frequency-selective fading channels, and treatment of polarized fading channels. The chapter continues with a discussion of simulation techniques for fading channels, including filtered white noise, sum of sinusoid techniques such as the classical Jakes’ technique, and techniques for generating multiple uncorrelated faded envelopes. Advanced simulation methodologies are discussed including wide-band simulation models such as the COST207 and COST259 models, symbol-spaced simulation models, and mobile-to-mobile simulation models. The chapter goes on to discuss modeling and simulation techniques for long term fading or shadowing. Finally, the chapter wraps up with theoretical and empirical path loss models, including the famous Okumura–Hata model, Lee’s model, various COST models, and 3GPP mm-wave path loss models.

For cellular radio systems the radio link performance is usually limited by interference rather than noise and, therefore, the probability of link outage due to co-channel interference (CCI) is of primary concern. The chapter begins with various approximations for the incoherent power sum of multiple log-normally shadowed interfering signals. The approximations are compared in terms of their accuracy. Afterwards, the probability of outage for log-normal/multiple log-normal links is considered. The chapter goes on to consider the outage probability for Ricean/multiple Rayleigh links without shadowing. Such an outage analysis may be more appropriate for wireless local area networks. The same is done for log-normal Nakagami/multiple log-normal Nakagami links, and log-normal Ricean/multiple log-normal Ricean faded links, where the signals are affected by both fading and shadowing. Such an outage analysis is appropriate for cellular systems where the mobile stations happen to be stationary.

Modulation is the process whereby message information is embedded into a radio frequency carrier. Such information can be transmitted in either the amplitude, frequency, or phase of the carrier, or a combination thereof. This chapter begins with the basis mathematical representation of digitally modulated signals. This is followed by a discussion of Nyquist pulse shaping, which is essentially for spectral control. Afterwards, the chapter considers a large number of digital modulation schemes that are commonly employed in wireless communication systems, including quadrature amplitude modulation, phase shift keying techniques, orthogonal modulation and variants, orthogonal frequency division multiplexing, and continuous phase modulation. The chapter concludes with a thorough treatment of the power spectrum of the various digitally modulated waveforms considered in the chapter.

Rayleigh fading converts an exponential dependency of the bit error probability on the average received bit energy-to-noise ratio into an inverse linear one, yielding a very large performance loss. Diversity is a very effective remedy that exploits the principle of providing the receiver with multiple independently faded replicas of the same information bearing signal. This chapter concentrates on antenna diversity techniques, although the mathematical concepts will readily apply to other types of diversity as well. Diversity systems consisting of a single transmit antenna and multiple receiver antennas are first considered. Various diversity combining techniques are treated including selective combining, maximal ratio combining, equal gain combining, switched combining, and differential detection with post-detection equal gain combining. Afterwards, optimum combining is considered which is useful for combating both fading and co-channel interference. The chapter then considers classical antenna beam-forming. Multiple-input multiple-output (MIMO) channels are introduced and, afterwards, various MIMO techniques are considered including the Alamouti transmit diversity scheme and spatial multiplexing and detection. Spatial modulation is considered next, where only one antenna in an array is activated. Finally, the chapter wraps up with a treatment of massive MIMO.

This chapter concentrates on the modeling of intersymbol interference (ISI) channels and the various signal processing methods for recovering digital information transmitted over such channels. The chapter begins with a treatment of ISI channel modeling, including a vector representation of digital signaling on ISI channels. The maximum likelihood receiver is then developed for ISI channels, leading to an equivalent model of the ISI channel known as the discrete-time white noise channel model. The effects of using fractional sampling or over-sampling at the receiver are also considered, where the sampling rate is an integer multiple of the modulated symbol rate. Afterwards, the various time domain equalization techniques are considered, including the linear zero-forcing and minimum mean-square-error equalizers, and the nonlinear decision feedback equalizer. Afterwards, sequence estimators are considered beginning with maximum likelihood sequence estimation (MLSE) and the Viterbi algorithm. Since the MLSE receiver can have high complexity for channels that have a long impulse response, some reduced complexity sequence estimation techniques are considered such as reduced state sequence estimation (RSSE) and delayed decision feedback sequence estimation (DDFSE). The chapter goes on to provide an analysis of the bit error rate performance of MLSE on static ISI channels and multipath-fading ISI channels, and fractionally-spaced MLSE receivers for ISI channels. Finally, the chapter provides a discussion of co-channel demodulation for digital signals on ISI channels, and concludes with a receiver structure that incorporates a combination of optimal combining and sequence estimation as implemented with the Viterbi algorithm.

Channel coding and interleaving techniques have long been used for combating noise, interference, jamming, fading, and other channel impairments. The basic idea of channel coding is to introduce controlled redundancy into the transmitted signals that is subsequently exploited at the receiver for error correction. There are many different types of error correcting codes, but historically they have been classified into block codes and convolutional/trellis codes. This chapter first starts with an introduction to block codes and space-time block codes. This is followed by a introduction to convolutional codes, and decoding algorithms for convolutional codes, including the Viterbi algorithm and BCJR algorithm. The chapter then introduces trellis-coded modulation, followed the performance analysis of convolutional and trellis codes on additive white Gaussian noise (AWGN) channels. Block and convolutional interleavers are discussed that are useful for coding on fading channels. This is followed by a consideration of the design and performance analysis of trellis codes on interleaved flat fading channels. Afterwards, the performance of space-time codes and the decoding of space-time codes is considered. Finally, the chapter wraps up with a treatment of parallel and serial turbo codes.

This chapter begins with a discussion of OFDM on frequency-selective channels, and describes how a cyclic guard interval can be used to completely remove any intersymbol interference (ISI) in a very efficient fashion provided that the length of the cyclic guard interval is at least as long as the length of the overall discrete-time channel impulse response. The performance of OFDM on static ISI channels and fading ISI channels is then considered, in cases where the length of the guard interval is less than the length of the overall discrete-time channel impulse response. In this case, residual ISI is present which is shown to be devastating to the performance of OFDM. An effective technique is then presented to mitigate residual ISI, called residual ISI cancellation (RISIC) that uses a combination of tail cancellation and cyclic reconstruction. The chapter then considers the combination of single-carrier modulation with frequency domain equalization (FDE), a technique known as single-carrier frequency domain equalization (SC-FDE). FDE is especially attractive on channels having long impulse responses where the complexity of time-domain equalizers can become prohibitive. Afterwards, a variety of topics related to OFDMA are considered. The use of OFDMA on both the forward and reverse link is covered, and issues such as sub-carrier allocation and time-domain windowing are considered. The chapter concludes with a discussion of single-carrier frequency division multiple access (SC-FDMA), including multiplexing methods and analysis of peak-to-average power ratio.

This chapter considers cellular frequency planning techniques for TDMA and OFDMA/SC-FDMA based cellular systems. The chapter begins with a discussion of basic cellular frequency planning techniques, including cell sectoring, cell splitting and reuse partitioning. This is followed by a treatment of issues related to frequency planning in OFDMA/SC-FDMA cellular networks. Afterwards, a novel TDMA hierarchical cellular architecture is considered that is based on the concept of cluster planning, where macrocells and microcells can share the same frequencies. Finally, the chapter wraps up with a treatment of macrodiversity TDMA architectures, where a mobile station is simultaneously served by multiple base stations.

This chapter considers capacity and performance of CDMA cellular systems. The chapter begins with a discussion of the power control mechanism in the CDMA reverse and forward links. Then the reverse and forward link capacity of CDMA cellular systems are treated, and the impact of imperfect power control demonstrated. The remainder of the chapter is devoted to hierarchical CDMA cellular architectures consisting of macrocells and underlaid macrocells, where both hierarchical layers use the entire system bandwidth. On the reverse link, this is accomplished by using macrodiversity maximal ratio combining where the signals received at multiple base stations (BSs) are coherently combined. On the forward link, only one BS is assumed to transmit to a given mobile station (MS) at any given time. The forward link transmit power is determined according to a neighboring cell pilot power scheme, where the forward transmit power to each MS is determined according to link conditions between the MS and surrounding BSs. It is shown that some improvement can be gained by using selective transmit diversity at the BSs on the forward link, i.e., to exploit forward channel macrodiversity.

This chapter is concerned with issues relating to link quality evaluation and handoff in cellular systems. The chapter begins by discussing several different types of signal strength based handoff algorithms. This is followed by a detailed treatment of temporal–spatial signal strength averaging. Guidelines are developed on the window length that is needed so that Ricean fading can be neglected in continuous- and discrete-time signal strength averaging. The need for velocity adaptive handoff algorithms is established and three different velocity estimators are presented. The velocity estimators are compared in terms of their sensitivity to the Rice factor, non-isotropic scattering, and additive white Gaussian noise. Afterwards, the velocity estimators are incorporated into a velocity adaptive handoff algorithm. Afterwards, an analytical treatment of conventional signal strength based hard handoff algorithms is undertaken, and the same is done for soft handoff algorithms. Finally, methods are discussed for carrier-to-interference plus noise ratio, C∕(I + N) measurements in TDMA cellular systems.

Channel assignment techniques are used extensively in frequency reuse systems to assign time-frequency resources to each user. There are many methods of allocating a channel upon a new call arrival or handoff attempt. A good channel allocation algorithm is the one that yields high spectral efficiency for a specified quality of service (including link quality, probability of new call blocking, and the probability of forced termination) and given degree of computational complexity and decentralization of control. It keeps the planned cell boundaries intact, allocates a channel to a MS quickly, maintains the best service quality for the MS at any instant, and relieves undesired network congestion. This chapter first discusses basic channel assignment techniques, then presents the details of some techniques. These include centralized dynamic channel assignment techniques such as the optimal maximum packing scheme. Afterwards, decentralized and fully decentralized dynamic channel assignment techniques are discussed. Borrowing schemes are discussed as well, where radio resources from neighboring cells can be borrowed to improve spectral efficiency and performance. The chapter goes on to discuss directed retry and moving direction based handoff schemes. The chapter concludes with some examples of dynamic channel assignment schemes for TDMA based cellular systems.