On the performance evaluation of ISI channels

The performance of finite intersymbol interference (ISI) channels in the presence of additive white Gaussian noise is evaluated by interpreting the ISI channel as a trellis code. Closed form results are obtained for ISI channels with one and two symbols of interference. An efficient algorithm is also introduced to evaluate the minimum free Euclidean distance of any ISI channel     

Turbo equalization of serially concatenated turbo codes using a predictive DFE-based receiver

This paper investigates the performance of various “turbo” receivers for serially concatenated turbo codes transmitted through intersymbol interference (ISI) channels. Both the inner and outer codes are assumed to be recursive systematic convolutional (RSC) codes. The optimum turbo receiver consists of an (inner) channel maximum a posteriori (MAP) decoder and a MAP decoder for the outer code. The channel MAP decoder operates on a “supertrellis” which incorporates the channel trellis and the trellis for the inner error-correcting code. This is referred to as the MAP receiver employing a SuperTrellis (STMAP). Since the complexity of the supertrellis in the STMAP receiver increases exponentially with the channel length, we propose a simpler but suboptimal receiver that employs the predictive decision feedback equalizer (PDFE). The key idea in this paper is to have the feedforward part of the PDFE outside the iterative loop and incorporate only the feedback part inside the loop. We refer to this receiver as the PDFE-STMAP. The complexity of the supertrellis in the PDFE-STMAP receiver depends on the inner code and the length of the feedback part. Investigations with Proakis B, Proakis C (both channels have spectral nulls with all zeros on the unit circle and hence cannot be converted to a minimum phase channel) and a minimum phase channel reveal that at most two feedback taps are sufficient to get the best performance. A reduced-state STMAP (RS-STMAP) receiver is also derived which employs a smaller supertrellis at the cost of performance.     

Space–Time Turbo Equalization With Successive Interference Cancellation for Frequency-Selective MIMO Channels

This paper addresses the issue of iterative space–time equalization for multiple-input–multiple-output (MIMO) frequency-selective fading channels. A new soft equalization concept based on successive interference cancellation (SIC) is introduced for a space–time bit-interleaved coded modulation (STBICM) transmission. The proposed equalizer allows us to separate intersymbol interference (ISI) and multiantenna interference (MAI) functions. Soft ISI is successively suppressed using a low-complexity suboptimum minimum mean square error (MMSE) criterion. The decoupling of ISI and MAI offers more flexibility in the design of the whole space–time equalizer. Different multiantenna detection criteria can be considered, ranging from simple detectors to the optimal maximum a posteriori (MAP) criterion. In particular, we introduce two soft equalizers, which are called SIC/SIC and SIC/MAP, and we show that they can provide a good performance-to-complexity tradeoff for many system configurations, as compared with other turbo equalization schemes. This paper also introduces an MMSE-based iterative channel state information (CSI) estimation algorithm and shows that attractive performance can be achieved when the proposed soft SIC space–time equalizer iterates with the MMSE-based CSI estimator.      

Adaptive Fair Subcarrier/Rate Allocation in Multirate OFDMA Networks: Radio Link Level Queuing Performance Analysis

This paper presents a semi-analytical methodology for radio link level performance analysis in a multirate "orthogonal frequency-division multiple-access" (OFDMA) network with adaptive fair rate allocation. Multirate transmission is assumed to be achieved through adaptive modulation, and fair rate allocation is based on the principle of generalized processor sharing to allocate the subcarriers adaptively among the users. The fair rate allocation problem is formulated as an optimization problem with the objective of maximizing system throughput while maintaining fairness (in terms of transmission rate) among the users. The "optimal" fair rate allocation is obtained by using the "Hungarian method." A heuristic-based approach, namely the "iterative approach," that is more implementation friendly is also presented. The throughput performance of the iterative fair rate allocation is observed to be as good as that of optimal fair rate allocation and is better than that of the static subcarrier allocation scheme. Also, the iterative fair allocation provides better fairness compared to that for each of the optimal and the static subcarrier allocation schemes. To this end, a queuing model is formulated to analyze radio link level performance measures such as packet dropping probability and packet transmission delay under the above rate allocation schemes. In this formulation, packet arrivals are modeled by the discrete Markov modulated Poisson process, which is flexible to model different types of traffic arrival patterns. The proposed framework for radio link level performance analysis of multirate OFDMA networks is validated by extensive simulations. Also, examples on the application of the proposed model for connection admission control and quality-of-service provisioning are illustrated     

Performance Improvement by Microdiversity for Wideband Signals in Frequency Selective Fading Indoor Channels with Co-Channel Interference

A comprehensive analytical bit-error-rate (BER) model is presented to analyse the performance of antenna-microdiversity for wideband BPSK modulated signals in the frequency selective fading multipath channel, specified by its complex impulse response. The model includes the disturbance by intersymbol interference (ISI) and co-channel interference (CCI), as well as the channels' impact on the carrier phase- and clock recovery in the receiver. The channel impulse responses at the antenna elements are determined by taking into account the direction of arrival of the individual paths. Computational BER- and SNIR-gain results (SNIR = signal-to-noise+interference-ratio) show that a substantial performance improvement is achieved with antenna combining for wideband signals which suffer ISI and/or CCI. For the indoor multipath channel with exponentially decaying power delay profile, the performance enhancement is compared for several antenna combining schemes. Quasi-coherent equal gain combining (QCEGC) is proposed as an novel EGC scheme based on a less accurate phase estimation technique. For wideband signals, QCEGC shows a slight performance degradation when compared to maximal ratio combining or minimum mean square error combining (MMSEC), but has a much lower implementation complexity. In the channel with CCI, where the best performance is achieved with MMSEC, QCEGC performs very poor.     

Iterative data detection and channel estimation for advanced TDMA systems

This letter presents a new receiver for Q-ary transmission, where all receiver blocks are embedded in an iterative structure. Packet data transmission in Global Systems for Mobile communications (GSM) and Enhanced Data rates for Global Evolution (EDGE) are considered as examples. A low-complexity soft-in-soft-out detector for EDGE is introduced and its modification suitable for iterative detection is derived. Application of iterative detection and channel estimation techniques in GSM/EDGE shows a significant performance enhancement. Additional improvement may be obtained if the iterative processing is applied to packet retransmission schemes.     

Reduced-complexity equalization techniques for ISI and MIMO wireless channels in iterative decoding

Two reduced-complexity soft-input soft-output trellis decoding techniques are presented in this paper for equalizing single-input single-output intersymbol interference (ISI) channels and multiple-input multiple-output (MIMO) frequency selective fading channels. Given a trellis representing an ISI channel, the soft-output M-algorithm (SOMA) reduces the complexity of equalization by retaining only the best M survivors at each trellis interval. The remaining survivors are discarded. The novelty of the SOMA is the use of discarded paths to obtain soft-information. Through a simple update-and-discard procedure, the SOMA extracts reliable soft-information from discarded paths which enables a large trellis to be successfully decoded with a relatively small value of M. To decode a trellis representing a MIMO frequency selective fading channel, two challenges are faced. Not only that the trellis has a large number of states, the number of branches per trellis interval is also enormous. The soft-output trellis/tree M-algorithm (SOTTMA) expands each trellis interval into a tree-like structure and performs the M-algorithm twice: once at each trellis interval to reduce the number of states and the other at each tree sub-level to remove unwanted branches. With the proposed technique, high-order trellises with million of branches per interval can be decoded with modest complexity.     

Coding for intersymbol interference channels-combined coding andprecoding

This paper describes a new coding scheme for transmission over intersymbol interference (ISI) channels. This scheme, called ISI coding, combines trellis coding with precoding (used to combat ISI). Like the recently introduced precoding scheme of Laroia, Tretter, and Farvardin (LTF), the ISI coder makes it possible to achieve both shaping and coding gains over ISI channels. By combining coding and precoding, however, the ISI coder makes the “precoding loss” independent of the number of coset partitions used to generate the trellis code. At high rates (large signal-to-noise ratio (SNR)), this makes it possible to approach the Shannon capacity of an ISI channel. The V.34 (formerly V.fast) international modem standard for high-speed (up to 28.8 kb/s) communication over voice-band telephone lines uses the version of the ISI coder described in Section IV of this paper     

Low-complexity iterative joint source-channel decoding for variable-length encoded Markov sources

In this paper, we present a novel packetized bit-level decoding algorithm for variable-length encoded Markov sources, which calculates reliability information for the decoded bits in the form of a posteriori probabilities (APPs). An interesting feature of the proposed approach is that symbol-based source statistics in the form of the transition probabilities of the Markov source are exploited as a priori information on a bit-level trellis. This method is especially well-suited for long input blocks, since in contrast to other symbol-based APP decoding approaches, the number of trellis states does not depend on the packet length. When additionally the variable-length encoded source data is protected by channel codes, an iterative source-channel decoding scheme can be obtained in the same way as for serially concatenated codes. Furthermore, based on an analysis of the iterative decoder via extrinsic information transfer charts, it can be shown that by using reversible variable-length codes with a free distance of two, in combination with rate-1 channel codes and residual source redundancy, a reliable transmission is possible even for highly corrupted channels. This justifies a new source-channel encoding technique where explicit redundancy for error protection is only added in the source encoder.     

Noncoherent iterative decoding of spectrally efficient coded modulations

In this paper, we consider possible solutions for noncoherent decoding of concatenated codes with spectrally efficient modulations. Two main classes of schemes are considered. A first class is obtained by concatenating parallel coding schemes with differential encoding. A second class considers serially concatenated coding structures and possible schemes derived from turbo trellis coded modulation (t-tcm), which do not employ differential encoding. In the first case, at the receiver side we consider separate detection and decoding, while in the second case we consider joint detection and decoding. The major problem connected with such an iterative decoding procedure is that taking into account an augmented channel memory leads to an intolerable trellis size, and hence to an impractical decoding complexity. Reduced-complexity techniques suited to iterative decoding become fundamental, and we consider a recently proposed state-reduction technique. This way, the performance of a coherent receiver is approached, by keeping the number of receiver states fixed.     

Iterative (turbo) soft interference cancellation and decoding forcoded CDMA

The presence of both multiple-access interference (MAI) and intersymbol interference (ISI) constitutes a major impediment to reliable communications in multipath code-division multiple-access (CDMA) channels. In this paper, an iterative receiver structure is proposed for decoding multiuser information data in a convolutionally coded asynchronous multipath DS-CDMA system. The receiver performs two successive soft-output decisions, achieved by a soft-input soft-output (SISO) multiuser detector and a bank of single-user SISO channel decoders, through an iterative process. At each iteration, extrinsic information is extracted from detection and decoding stages and is then used as a priori information in the next iteration, just as in turbo decoding. Given the multipath CDMA channel model, a direct implementation of a sliding-window SISO multiuser detector has a prohibitive computational complexity. A low-complexity SISO multiuser detector is developed based on a novel nonlinear interference suppression technique, which makes use of both soft interference cancellation and instantaneous linear minimum mean-square error filtering. The properties of such a nonlinear interference suppressor are examined, and an efficient recursive implementation is derived. Simulation results demonstrate that the proposed low complexity iterative receiver structure for interference suppression and decoding offers significant performance gain over the traditional noniterative receiver structure. Moreover, at high signal-to-noise ratio, the detrimental effects of MAI and ISI in the channel can almost be completely overcome by iterative processing, and single-user performance can be approached     

Adaptive Generator Sequence Selection in Multilevel Space–Time Trellis Codes

It has been shown that multilevel space–time trellis codes (MLSTTCs) designed by combining multilevel coding (MLC) with space–time trellis codes (STTCs) can provide improvement in diversity gain and coding gain of the STTCs. MLSTTCs assume perfect channel state information (CSI) at receiver and no knowledge of CSI at transmitter. Weighted multilevel space–time trellis codes (WMLSTTCs), designed by combining MLSTTCs and perfect CSI at transmitter are capable of providing improvement in coding gain of MLSTTCs. In this paper, we present improvement in performance of MLSTTCs by using channel feedback information from the receiver for adaptive selection of generator sequences. The selected generator sequences are used for encoding the component STTCs. The receiver compares current channel profile at receiver with a set of predetermined channel profiles, and sends an index of a predefined channel profile closest to the current channel profile to the transmitter. The transmitter selects a code set that matches best with the current channel profile at receiver using the index. The selected code set having different sets of generator sequences is used by STTC encoders to generate dynamic space–time trellis codes (DSTTCs). The DSTTCs act as component codes in multilevel coding for generating new codes henceforth referred to as multilevel dynamic space–time trellis codes (MLDSTTCs). Analysis and simulation results show that MLDSTTCs provide improvement in performance over MLSTTCs.     

Combined turbo detection and decoding for unknown ISI channels

We present two decoding structures which combine turbo detection and decoding, allowing communication in the presence of intersymbol interference (ISI). The first one treats the ISI as another constituent decoder which participates in the exchange of extrinsic information, and performs slightly worse than the second structure, which combines the trellis representing each one of the constituent encoders with the ISI trellis. We show that for both methods, it is possible to obtain good performance, even when no a priori information about the ISI channel is available to the decoder.     

On Joint Source and Channel Coding Using Trellis Coded CPM: Analytical Bounds on the Channel Distortion

Joint source and channel coding (JSCC) using trellis coded quantization (TCQ) in conjunction with trellis coded continuous phase modulation (CPM) is studied. The channel is assumed to be the additive white gaussian noise (AWGN) channel. Analytical bounds on the channel distortion for the investigated systems with maximum-likelihood sequence detection (MLSD) are developed. The bounds are based on the transfer function technique, which was modified and generalized to include continuous-amplitude discrete-time signals. For a memoryless uniform source, the constructed bounds for the investigated systems are shown to be asymptotically tight for increasing channel signal-to-noise ratio (SNR) values. For a memoryless nonuniform source, the constructed bounds are not as tight as the one for the uniform source, however, it still can be used as an indication to how the system performs. It is concluded that the minimum Euclidean distance of the system alone is not enough to evaluate the performance of the considered systems. The number of error events having minimum Euclidean distance and the total distortion caused by those error events also affect the asymptotic performance. This work provides an analysis tool for the investigated systems. The analysis method is very general. It may be applied to any trellis based JSCC schemes.     

Highly scalable JPEG image transmission with unequal error protection and optimal feedback

This paper investigates the performance of three different Unequal Error Protection (UEP) schemes for progressive JPEG image transmission using delay-constrained hybrid ARQ, with iterative bit and symbol combining. The first UEP scheme considers only the optimization of channel code-rates and keeps the number of retransmissions fixed for all the subbands of the image. The second one optimizes both the channel code-rates and retransmissions, while the third only considers the optimal allocation of retransmission requests. The UEP schemes are designed with two different coding techniques. The first one employs Rate Compatible Punctured Turbo Codes (RCPT) with iterative bit combining and, is suitable for applications requiring high power efficiency. For the second one we propose a new coding strategy, Rate Compatible Punctured Turbo Trellis Coded Modulation (RCPTTCM) with iterative symbol combining, which provides high scalability and bandwidth efficiency. Gains of over 9 dB in Peak-Signal-to-Noise-Ratio are obtained with the UEP schemes as compared to their corresponding Equal Error Protection (EEP) schemes.     

Performance of trellis codes for a class of equalized ISI channels

The performance of trellis codes is examined for a class of intersymbol interference (ISI) channels that occur in high-frequency radio systems. The channels considered are characterized by in-band spectral nulls and by a rapid time variation. The baseline modulation technique is 4QAM (four-point quadrature amplitude modulation). When spectral nulls are absent, performance of fractionally spaced linear equalizers and trellis decoders is found to be near ideal and to be better than using symbol-spacing in the equalizer. However, error propagation in the feedback path, resulting from equalizer-based decisions, ruins the performance of the combination of decision-feedback equalizers and trellis decoders when spectral nulls are present. Their performance can be improved by using fractionally spaced feedforward equalizer sections and by designing the decoder to compensate for ISI. Rate 2/3 codes are found to outperform rate 1/2 codes in error performance     

A comparison of trellis coded and Reed-Solomon coded hybrid-ARQ protocols over slowly fading Rayleigh channels

The performance of trellis coded and Reed-Solomon coded ARQ error control systems over slowly fading Rayleigh channels are compared and contrasted in this paper. First, a two-code CRC-TCM type-I hybrid-ARQ scheme based on separate error correction and error detection codes is compared to a one-code Reed-Solomon protocol in which retransmission requests are generated within the decoding process. The performance of the associated packet combining protocols is also compared. It is shown that for similar levels of complexity, a onecode Reed-Solomon approach offers both better throughput and reliability performance than the TCM schemes in almost all cases.     

Turbo equalization via constrained-delay APP estimation with decision feedback

We consider turbo equalization for intersymbol interference (ISI) channels, wherein soft symbol decisions generated by the channel detector are iteratively exchanged with the outer error-correction decoder based on the turbo principle. Our work is based on low-complexity suboptimal soft-output channel detection using a constrained-delay (CD) a posteriori probability (APP) algorithm. Central to the proposed idea is the incorporation of effective decision-feedback schemes, which significantly reduce complexity while providing immunity against error propagation that typically plagues decision-feedback schemes. We observe that the effect of decision feedback is quite different on turbo equalization versus traditional, hard-decision-generating and noniterative equalization. In particular, we demonstrate that when the feedback scheme applied is inadequate for the given equalizer parameters and ISI condition, the extrinsic information generated by the equalizer becomes distinctly non-Gaussian, and the quality of soft information, as monitored by the trajectory of mutual information, fails to improve in the iterative process. We identify parameters of feedback-based CD-APP schemes that offer favorable complexity/performance tradeoffs, compared with existing turbo-equalization techniques.     

OFDMA-CDM performance enhancement by combining H-ARQ and interference cancellation

In this paper, superimposed packet allocation for orthogonal frequency-division multiple-access code-division multiplexing (OFDMA-CDM) is presented, where each transmitted packet is associated with one spreading code. An iterative algorithm which is a combination of parallel interference cancellation and hybrid automatic repeat request (H-ARQ) based on soft value combining (SVC) is proposed, and its performance is studied and compared with other existing H-ARQ schemes. The proposed algorithm exploits the reliability information of erroneously received copies of the same data packet to improve the performance of interference cancellation. The interference of correctly received packets is ideally reconstructed and subtracted. Thus, the overall system performance improves iteratively. As a result, the proposed algorithm outperforms conventional H-ARQ based on SVC, as well as H-ARQ based on maximum ratio combining.     

Performance evaluation of coded modulation schemes based on binarylattices

We describe computational techniques for the evaluation of error probability of modulation schemes based on binary lattices and multilevel coding. These techniques stem from the representation of a binary lattice in the form of a trellis whose structure depends on the block codes on which the binary lattice is based. Multilevel coded-modulation schemes can also be described through a trellis; by combining with this the trellis structure of the lattice constellation we obtain a single trellis that can be used for maximum-likelihood decoding using the Viterbi algorithm and for computing the error probability. An upper bound to error probability can be obtained from the transfer function of the trellis with suitable labels, and is applicable to both maximum-likelihood and staged decoding