
- •Contents
- •Preface
- •1 Spread spectrum signals and systems
- •1.1 Basic definition
- •1.2 Historical sketch
- •2 Classical reception problems and signal design
- •2.1 Gaussian channel, general reception problem and optimal decision rules
- •2.2 Binary data transmission (deterministic signals)
- •2.3 M-ary data transmission: deterministic signals
- •2.4 Complex envelope of a bandpass signal
- •2.5 M-ary data transmission: noncoherent signals
- •2.6 Trade-off between orthogonal-coding gain and bandwidth
- •2.7 Examples of orthogonal signal sets
- •2.7.1 Time-shift coding
- •2.7.2 Frequency-shift coding
- •2.7.3 Spread spectrum orthogonal coding
- •2.8 Signal parameter estimation
- •2.8.1 Problem statement and estimation rule
- •2.8.2 Estimation accuracy
- •2.9 Amplitude estimation
- •2.10 Phase estimation
- •2.11 Autocorrelation function and matched filter response
- •2.12 Estimation of the bandpass signal time delay
- •2.12.1 Estimation algorithm
- •2.12.2 Estimation accuracy
- •2.13 Estimation of carrier frequency
- •2.14 Simultaneous estimation of time delay and frequency
- •2.15 Signal resolution
- •2.16 Summary
- •Problems
- •Matlab-based problems
- •3 Merits of spread spectrum
- •3.1 Jamming immunity
- •3.1.1 Narrowband jammer
- •3.1.2 Barrage jammer
- •3.2 Low probability of detection
- •3.3 Signal structure secrecy
- •3.4 Electromagnetic compatibility
- •3.5 Propagation effects in wireless systems
- •3.5.1 Free-space propagation
- •3.5.2 Shadowing
- •3.5.3 Multipath fading
- •3.5.4 Performance analysis
- •3.6 Diversity
- •3.6.1 Combining modes
- •3.6.2 Arranging diversity branches
- •3.7 Multipath diversity and RAKE receiver
- •Problems
- •Matlab-based problems
- •4 Multiuser environment: code division multiple access
- •4.1 Multiuser systems and the multiple access problem
- •4.2 Frequency division multiple access
- •4.3 Time division multiple access
- •4.4 Synchronous code division multiple access
- •4.5 Asynchronous CDMA
- •4.6 Asynchronous CDMA in the cellular networks
- •4.6.1 The resource reuse problem and cellular systems
- •4.6.2 Number of users per cell in asynchronous CDMA
- •Problems
- •Matlab-based problems
- •5 Discrete spread spectrum signals
- •5.1 Spread spectrum modulation
- •5.2 General model and categorization of discrete signals
- •5.3 Correlation functions of APSK signals
- •5.4 Calculating correlation functions of code sequences
- •5.5 Correlation functions of FSK signals
- •5.6 Processing gain of discrete signals
- •Problems
- •Matlab-based problems
- •6 Spread spectrum signals for time measurement, synchronization and time-resolution
- •6.1 Demands on ACF: revisited
- •6.2 Signals with continuous frequency modulation
- •6.3 Criterion of good aperiodic ACF of APSK signals
- •6.4 Optimization of aperiodic PSK signals
- •6.5 Perfect periodic ACF: minimax binary sequences
- •6.6 Initial knowledge on finite fields and linear sequences
- •6.6.1 Definition of a finite field
- •6.6.2 Linear sequences over finite fields
- •6.6.3 m-sequences
- •6.7 Periodic ACF of m-sequences
- •6.8 More about finite fields
- •6.9 Legendre sequences
- •6.10 Binary codes with good aperiodic ACF: revisited
- •6.11 Sequences with perfect periodic ACF
- •6.11.1 Binary non-antipodal sequences
- •6.11.2 Polyphase codes
- •6.11.3 Ternary sequences
- •6.12 Suppression of sidelobes along the delay axis
- •6.12.1 Sidelobe suppression filter
- •6.12.2 SNR loss calculation
- •6.13 FSK signals with optimal aperiodic ACF
- •Problems
- •Matlab-based problems
- •7 Spread spectrum signature ensembles for CDMA applications
- •7.1 Data transmission via spread spectrum
- •7.1.1 Direct sequence spreading: BPSK data modulation and binary signatures
- •7.1.2 DS spreading: general case
- •7.1.3 Frequency hopping spreading
- •7.2 Designing signature ensembles for synchronous DS CDMA
- •7.2.1 Problem formulation
- •7.2.2 Optimizing signature sets in minimum distance
- •7.2.3 Welch-bound sequences
- •7.3 Approaches to designing signature ensembles for asynchronous DS CDMA
- •7.4 Time-offset signatures for asynchronous CDMA
- •7.5 Examples of minimax signature ensembles
- •7.5.1 Frequency-offset binary m-sequences
- •7.5.2 Gold sets
- •7.5.3 Kasami sets and their extensions
- •7.5.4 Kamaletdinov ensembles
- •Problems
- •Matlab-based problems
- •8 DS spread spectrum signal acquisition and tracking
- •8.1 Acquisition and tracking procedures
- •8.2 Serial search
- •8.2.1 Algorithm model
- •8.2.2 Probability of correct acquisition and average number of steps
- •8.2.3 Minimizing average acquisition time
- •8.3 Acquisition acceleration techniques
- •8.3.1 Problem statement
- •8.3.2 Sequential cell examining
- •8.3.3 Serial-parallel search
- •8.3.4 Rapid acquisition sequences
- •8.4 Code tracking
- •8.4.1 Delay estimation by tracking
- •8.4.2 Early–late DLL discriminators
- •8.4.3 DLL noise performance
- •Problems
- •Matlab-based problems
- •9 Channel coding in spread spectrum systems
- •9.1 Preliminary notes and terminology
- •9.2 Error-detecting block codes
- •9.2.1 Binary block codes and detection capability
- •9.2.2 Linear codes and their polynomial representation
- •9.2.3 Syndrome calculation and error detection
- •9.2.4 Choice of generator polynomials for CRC
- •9.3 Convolutional codes
- •9.3.1 Convolutional encoder
- •9.3.2 Trellis diagram, free distance and asymptotic coding gain
- •9.3.3 The Viterbi decoding algorithm
- •9.3.4 Applications
- •9.4 Turbo codes
- •9.4.1 Turbo encoders
- •9.4.2 Iterative decoding
- •9.4.3 Performance
- •9.4.4 Applications
- •9.5 Channel interleaving
- •Problems
- •Matlab-based problems
- •10 Some advancements in spread spectrum systems development
- •10.1 Multiuser reception and suppressing MAI
- •10.1.1 Optimal (ML) multiuser rule for synchronous CDMA
- •10.1.2 Decorrelating algorithm
- •10.1.3 Minimum mean-square error detection
- •10.1.4 Blind MMSE detector
- •10.1.5 Interference cancellation
- •10.1.6 Asynchronous multiuser detectors
- •10.2 Multicarrier modulation and OFDM
- •10.2.1 Multicarrier DS CDMA
- •10.2.2 Conventional MC transmission and OFDM
- •10.2.3 Multicarrier CDMA
- •10.2.4 Applications
- •10.3 Transmit diversity and space–time coding in CDMA systems
- •10.3.1 Transmit diversity and the space–time coding problem
- •10.3.2 Efficiency of transmit diversity
- •10.3.3 Time-switched space–time code
- •10.3.4 Alamouti space–time code
- •10.3.5 Transmit diversity in spread spectrum applications
- •Problems
- •Matlab-based problems
- •11 Examples of operational wireless spread spectrum systems
- •11.1 Preliminary remarks
- •11.2 Global positioning system
- •11.2.1 General system principles and architecture
- •11.2.2 GPS ranging signals
- •11.2.3 Signal processing
- •11.2.4 Accuracy
- •11.2.5 GLONASS and GNSS
- •11.2.6 Applications
- •11.3 Air interfaces cdmaOne (IS-95) and cdma2000
- •11.3.1 Introductory remarks
- •11.3.2 Spreading codes of IS-95
- •11.3.3 Forward link channels of IS-95
- •11.3.3.1 Pilot channel
- •11.3.3.2 Synchronization channel
- •11.3.3.3 Paging channels
- •11.3.3.4 Traffic channels
- •11.3.3.5 Forward link modulation
- •11.3.3.6 MS processing of forward link signal
- •11.3.4 Reverse link of IS-95
- •11.3.4.1 Reverse link traffic channel
- •11.3.4.2 Access channel
- •11.3.4.3 Reverse link modulation
- •11.3.5 Evolution of air interface cdmaOne to cdma2000
- •11.4 Air interface UMTS
- •11.4.1 Preliminaries
- •11.4.2 Types of UMTS channels
- •11.4.3 Dedicated physical uplink channels
- •11.4.4 Common physical uplink channels
- •11.4.5 Uplink channelization codes
- •11.4.6 Uplink scrambling
- •11.4.7 Mapping downlink transport channels to physical channels
- •11.4.8 Downlink physical channels format
- •11.4.9 Downlink channelization codes
- •11.4.10 Downlink scrambling codes
- •11.4.11 Synchronization channel
- •11.4.11.1 General structure
- •11.4.11.2 Primary synchronization code
- •11.4.11.3 Secondary synchronization code
- •References
- •Index
Spread spectrum signals and systems |
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The definition given is in fact the one which has been widely and long since adopted in the systems of radar-akin philosophy, but it is also consistent with data communication problems. That is why we will rely on it in the following text.
1.2 Historical sketch
The history of spread spectrum covers over six decades and may serve as a topic of separate study. The reader interested in learning the chronology of the key events can address in-depth (albeit focused almost totally on US developments) surveys in [9,10]. Here we limit ourselves to only a very brief mention of the main historical landmarks.
Probably the first patent on the radar, which in modern terminology may be without doubt treated as spread spectrum, was obtained by G. Guanella in 1938. During and after World War II, intensive research in radar spread spectrum systems had been undertaken in Germany, the USA, the UK and the USSR. In parallel with technological and technical advancements, numerous solid theoretical investigations had been conducted into the precision and signal resolution of radar. The most influential and deep results in this regard were published by P. M. Woodward in his 1953 book. It should be noted in passing that many of these results were explainable based on fundamental works by C. Shannon and V. A. Kotelnikov between 1946 and 1948, the role of which thereby goes far beyond only ‘pure’ data communication applications.
Certainly, for a long time a great deal of information on new practical developments in spread spectrum radar and navigation was classified, because military and intelligence services supervised the great majority of projects. However, many ideas were getting widely known as soon as they were realized in systems of mass-scale usage. A good example of this is the world-wide navigation system Loran-C deployed in the early 1960s in which ground-based longwave radio beacons transmitted ‘genuine’ spread spectrum (PSK) signals having time–frequency product WT ¼ 16. To imagine how viable this system appeared to be, it is enough to stress that with continual modernization and numerous improvements it has managed to remain in operation to see the third millennium.
Another giant step in the practical implementation of the spread spectrum concept in time–distance measuring systems was taken with the creation of the 2G space-based global navigation networks GPS (USA) and GLONASS (USSR/Russia) in the 1980s and early 1990s. Signals with very large time–frequency products, measured in the thousands, are at the heart of these systems, which today constitute an integral part of human civilization as satellite television and mobile radio.
The earliest works in spread spectrum applications to data transmission were primarily aimed at speech masking and communication protection. They started again before World War II in Germany and were soon taken up in the USA, the USSR and elsewhere. An intriguing action of the novel The First Circle by Alexander Solzhenitsyn unfolds in the special Soviet jail where convicted scholars and engineers are collected together to elaborate the noise-masked speech transmission system.
Among the turning points in spread spectrum communication, the RAKE algorithm proposed by R. Price and P. Green (1957) should be pointed to, which marked the beginning of the direction later called multipath diversity. Works in the 1960s by
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Spread Spectrum and CDMA |
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S. Golomb, N. Zierler, R. Gold, T. Kasami and others in the field of discrete sequences with special correlation properties played a crucial role in the formation of spread spectrum technology and numerous practical achievements.
The commercial spread spectrum era started around the late 1970s, at the time when the mobile telephone began its triumphant conquest of the world. The first proposals for CDMA cellular networks in the USA and Europe (1978–1980) yielded to alternative projects, which later evolved into the GSM and DAMPS standards. However, in the mid 1990s the 2G standard IS-95 was put forward, resting on a fully spread spectrum/ CDMA platform. At a cosmic pace, networks of this standard (later named cdmaOne) gained wide recognition in America, Asia and the former Soviet Union countries. The great success of IS-95, as well as careful analysis and further experiments, had led to acceptance of the spread spectrum/CDMA philosophy as the basic platform for the major 3G mobile radio specifications: UMTS and cdma2000. Both of them are now in the pre-operational stage and undoubtedly will become the main mobile communication instruments for the next decades.
To conclude this introductory chapter, there are a few words about the development of spread spectrum technology in the Soviet Union and later in Russia. Surveys published in the West usually report only a little on Soviet research in this area. There are a number of objective reasons for this, characteristic of the cold war period: the country’s self-isolation, strict limits on the contacts of Soviet specialists with their foreign colleagues and publications abroad, excessive and often needless secrecy etc. The language barrier has also been a serious impediment. But as a matter of fact, Soviet advancement in the spread spectrum field between the 1950s and the 1990s was very up-to-date and quite competitive with developments in the USA and Europe. Works by D. E. Vackman, Ya. D. Shirman, M. B. Sverdlick (spread spectrum radar signal design and processing), I. N. Amiantov and L. E. Varakin (spread spectrum communications) were pioneering in many respects and recruited generations of young professionals into this attractive and absorbing research area.