
- •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

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preferable for contact. In the latter case the network may order MS switching to another BS, which is done easily, since the receiver is already tracking its signal (soft handover).
11.3.4 Reverse link of IS-95
According to the logical content of the data transmitted over the reverse channel every MS operates on one of two types of channels:
. traffic channel
. access channel.
11.3.4.1 Reverse link traffic channel
Figure 11.5 presents a simplified structure of the reverse traffic channel. The MStransmitted bit stream (digitized speech from a vocoder, computer data etc.) with inserted CRC symbols is divided into 20 ms frames, where 8 tail bits are then inserted for zero-resetting of a convolutional encoder at the start of every encoded frame. As a result the nominal rate of data at the encoder input is 9.6 kbps, but for reduced voice activity three lower rates (4.8, 2.4 and 1.2 kbps) are also employed, in the same way as in the forward link. Due to the asynchronous nature of the reverse link, MAI—unlike in the forward link—would exist even in the hypothetical absence of multipath effects (see footnote 2). This qualitatively justifies the greater strain interference condition of the IS-95 reverse link, explaining why it exploits a convolutional code with higher error correction capability in combination with subsequent 64-ary orthogonal modulation. Since increasing the constraint length c would entail undesirable codec complications, its accepted value is the same as in the forward link ( c ¼ 9), reduction of the code rate to 1/3 being a payment for better distance properties. With such a code rate the output codestream rate is 28.8 kbps independently of input bit stream rate: the symbol repetition explained earlier for a forward channel is administered in the reverse link as well.
An individual 20 ms frame of a codestream (576 bits) is divided into 16 power control groups of 36 bits (1.25 ms) each. An interleaver operating over the frame uses a 32 18 matrix, where the codestream is written column-wise. The reading runs row-wise, every pair of odd and the next even rows forming one PCG. However, consecutive pairs of
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Interleaver |
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orthogonal |
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encoder |
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modulator |
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Figure 11.5 Simplified structure of IS-95 reverse traffic channel
354 |
Spread Spectrum and CDMA |
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rows are read according to a pattern providing adjacency of PCG repeating each other (due to encoded symbol repetition) whenever the raw datastream rates are smaller than 9.6 kbps (i.e. 4.8, 2.4 and 1.2 kbps). For example, when the raw rate is 4.8 kbps every even PCG contains repetition of the same interleaved code symbols as the previous; for the datastream rate 2.4 kbps the groups with numbers 4i þ 2, 4i þ 3, 4i þ 4 are replicas of the group number 4i þ 1, etc. Such an order is convenient for further lowering of the average transmitted power proportionally to the rate reduction, which is realized in the reverse link slightly differently as compared to the forward link (see below).
The codestream from the interleaver is fed to the 64-ary orthogonal modulator, meaning that every 6-symbol block treated as a binary 6-digit number selects one of 64 orthogonal signals (a Walsh function of this number). This gives an extra coding gain (up to three times asymptotically; see Section 2.6) above that of convolutional coding. Since every 6 input binary symbols are now replaced by 64 binary symbols, the stream of chips at the orthogonal modulator output becomes 64/6 ¼ 32/3 times faster (307.2 kcps). Let us stress that Walsh functions in the reverse link bear no channelization functions and only implement spread spectrum orthogonal coding for data transmission, as discussed in Section 2.7.3.
The next step in forming a traffic channel is spreading, i.e. modulo 2 summation of the binary symbol stream after the orthogonal modulator with the offset long-code sequence. Since the long code is a chip stream with rate 1.2288 Mcps, there are 4 longcode chips per Walsh symbol or 256 long-code chips per Walsh signal at the orthogonal modulator output. The BS receiver after despreading uses a 64-channel correlator bank, each channel being tuned to one of the Walsh signals, and decides in favour of the Walsh signal referencing the correlator with the strongest response. As such, a processing interval covers the whole Walsh function duration, i.e. 256 long-code chips, and the spreading factor of the reverse link appears to be 256. A long code is unique, strictly specified by the standard, and it is user-specific masks (time-offsets of the code) that secure CDMA separation of different users. Thus, we encounter here the strategy of asynchronous CDMA discussed in Section 7.4. Of course, these offsets should be properly assigned to have no risk of synchronous arrival at the BS of signals from two MSs migrating freely over the whole coverage zone. The value of offset is a current MS identity rendered to it by the network similarly to the channel carrier in FDMA. In parallel with the CDMA channelization, the user-specific mask provides the encryption (scrambling) of the stream after orthogonal modulator. Due to the enormous length of the long code, it is not an easy task for an unauthorized interceptor, who does not know the user’s mask, to synchronize a local long-code generator to the intercepted signal and despread (thereby descramble and decrypt) the data.
The operation of mapping logical f0, 1g symbols onto the real modulation alphabet f 1g is the same as before and does not require any special comment.
One of the primary requirements for MS handset is a long enough battery lifetime. From this angle a linear power amplifier consuming higher average power is less attractive than a nonlinear (operating in a keying mode) one. That is the reason why in the MS transmitter average power reduction is achieved not by lowering an instant power, but alternatively by transmitting only one PCG of all those that replicate each other. For example, with a raw rate 2.4 kbps there are quadruplets of identical PCGs and only one of them is transmitted, while the transmitter is cut off during the three

Operational wireless spread spectrum systems |
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20 ms frame = 16 PCG
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PCG 1.25 ms
Figure 11.6 Example MS transmission pattern for the raw rate 4.8 kbps
others. Certainly, this makes MS emission discontinuous. Randomization of the positions of discarded PCGs (data burst randomization) enables better averaging of discontinuous MAI at the BS. The pseudorandom pattern of gating off the PCG inside any frame is determined by the last 14 chips of a user’s mask, i.e. offset long-code replica, at the end of the previous frame. The rule defined in the specification for every particular raw rate recalculates values of these chips (as binary digits) into the positions of erased PCGs. Figure 11.6, where identical numbers mark replicated PCGs, and shaded and dashed rectangles correspond to transmitted and erased PCGs, shows an example transmission pattern for raw rate 4.8 kbps. We may treat the sequence after the data burst randomizer as ternary with symbols f1g and zero corresponding to active and pausing transmitter, respectively.
11.3.4.2 Access channel
MS uses an access channel when responding to a notification about an incoming call in the idle state and when it either needs to register on the network or initiate a call. The procedures of framing, convolutional encoding, orthogonal modulation, interleaving and long-code spreading in the access channel are basically similar to those of the reverse traffic channel. Of course, no voice data is transmitted through this channel, so no rate/power control according to voice activity is performed. One of the specific features of the access channel relates to initiating access by MS. Not knowing precisely the propagation conditions in the reverse link, the MS starts by sending probe signals of low strength, gradually increasing the signal level with every next attempt until it obtains the BS confirmation that the connection is established. Probe signals are sent in a burst mode with randomized intervals to reduce the probability of colliding requests from several users, because it is not impossible that at the access stage different MSs have the same long code masks.
11.3.4.3 Reverse link modulation
MS can never use both traffic and access channels simultaneously, therefore there is no need for channel signal summation at the modulator input as there was in the forward channel. Traffic or access channel output is immediately fed in parallel into in-phase/ quadrature branches, differing from those of Figure 11.4 in the following details. First, offsetting short codes PN-1 and PN-2 to identify BS is now needless (every mobile has its own unique identity—long code mask—all over the coverage zone), and even inconvenient