Without being necessary to pack multiple antennas per terminal, cooperation among distributed single-antenna nodes offers resilience to shadowing and can, in principle, enhance the performance of wireless communication networks by exploiting the available space diversity. Enabling the latter however, calls for practically implementable protocols to cope with errors at relay nodes so that simple receiver processing can collect the diversity at the destination. To this end, we derive in this paper a class of strategies whereby decoded bits at relay nodes are scaled in power before being forwarded to the destination. The scale is adapted to the signal-to-noise-ratio (SNR) of the source-relay and the intended relay-destination links. With maximum ratio combining (MRC) at the destination, we prove that such link-adaptive regeneration (LAR) strategies effect the maximum possible diversity while requiring simple channel state information that can be pragmatically acquired at the relay. In addition, LAR exhibits robustness to quantization and feedback errors and leads to efficient use of power both at relay as well as destination nodes. Analysis and corroborating simulations demonstrate that LAR relays are attractive across the practical SNR range; they are universally applicable to multibranch and multi-hop uncoded or coded settings regardless of the underlying constellation; and outperform existing alternatives in terms of error performance, complexity and bandwidth efficiency.

In communication systems employing a serially concatenated cyclic redundancy check (CRC) code along with a convolutional code (CC), erroneous packets after CC decoding are usually discarded. The list Viterbi algorithm (LVA) and the iterative Viterbi algorithm (IVA) are two existing approaches capable of recovering erroneously decoded packets. We here employ a soft decoding algorithm for CC decoding, and introduce several schemes to identify error patterns using the posterior information from the CC soft decoding module. The resultant iterative decoding-detecting (IDD) algorithm improves error performance by iteratively updating the extrinsic information based on the CRC parity check matrix. Assuming errors only happen in unreliable bits characterized by small absolute values of the log-likelihood ratio (LLR), we also develop a partial IDD (P-IDD) alternative which exhibits comparable performance to IDD by updating only a subset of unreliable bits. We further derive a soft-decision syndrome decoding (SDSD) algorithm, which identifies error patterns from a set of binary linear equations derived from CRC syndrome equations. Being noniterative, SDSD is able to estimate error patterns directly from the decoder output. The packet error rate (PER) performance of SDSD is analyzed following the union bound approach on pairwise errors. Simulations indicate that both IDD and IVA are better tailored for single parity check (PC) codes than for CRC codes. SDSD outperforms both IDD and LVA with weak CC and strong CRC. Applicable to AWGN and flat fading channels, our algorithms can also be extended to turbo coded systems.

A general framework is developed for multi-source cooperation (MSC) protocols to improve diversity and spectral efficiency relative to repetition based alternatives that rely on single-source cooperation. The novel protocols are flexible to balance tradeoffs among diversity, spectral efficiency and decoding-complexity. Users are grouped in clusters and follow a two-phase MSC protocol which involves time division multiple access (TDMA) to separate users within a cluster, and code division multiple access (CDMA) used to separate clusters. An attractive protocol under the general MSC framework relies on distributed complex field coding (DCFC) to enable diversity order equal to the number of users per cluster. Cluster separation based on orthonormal spreading sequences leads to spectral efficiency 1/2. When the number of clusters exceeds the amount of spreading, spectral efficiency can be enhanced without sacrificing diversity, at the expense of controllable increase in complexity. Simulations corroborate our analytical claims

Recently, error control codes, including convolutional codes, have been used in multi-source cooperation (MSC) networks to provide higher diversity and code rates relative to repetition-based single source cooperation alternatives. For an MSC network with K active users, it has been established that the maximum diversity order is less than K for any error control code with code rate R > 1/K. This paper introduces distributed complex field coding (DCFC) in MSC networks. Theoretical analysis reveals that DCFC-MSC is capable of enabling full diversity order equal to K, at a fixed rate 1/2. Simulations verify that DCFC-MSC can improve system performance markedly.

In communication systems employing a serially concatenated cyclic redundancy check (CRC) code along with a convolutional code (CC), erroneous packets after CC decoding are usually discarded. The list Viterbi algorithm (LVA) and the iterative Viterbi algorithm (IVA) are two existing approaches capable of recovering erroneously decoded packets. We first propose an iterative log-MAP (ILM) algorithm improves error performance by iteratively updating the extrinsic information based on the CRC parity check matrix. We further derive a soft-decision syndrome decoding (SDSD) algorithm, which identifies error patterns from a set of binary linear equations derived from CRC syndrome equations. Being non-iterative, SDSD is able to estimate error patterns directly from the decoder output. The packet error rate (PER) performance of SDSD is analyzed following the union bound approach on pairwise errors. Simulations indicate that SDSD outperforms both ILM and LVA with weak CC and strong CRC. Applicable to AWGN and flat fading channels, our algorithms can also be extended to turbo coded systems.

Hard sphere decoding (HSD) has well-appreciated merits for near-optimal demodulation of multiuser, block single-antenna or multi-antenna transmissions over multi-input multi-output (MIMO) channels. At increased complexity, a soft version of sphere decoding (SD), so-termed list SD (LSD), has been recently applied to coded layered space-time (LST) systems enabling them to approach the capacity of MIMO channels. By introducing a novel bit-level multi-stream coded LST transmitter along with a soft-to-hard conversion at the decoder, we show how to achieve the near-capacity performance of LSD, and even outperform it as the size of the block to be decoded (M) increases. Specifically, for binary real LST codes, we develop exact max-log-based SD schemes with M + 1 HSD steps, and an approximate alternative with only one HSD step to trade off performance for average complexity. These schemes apply directly to the real and imaginary parts of quaternary phase-shift keying signaling, and also to quadrature amplitude modulation signaling after incorporating an appropriate interference estimation and cancellation module. We corroborate our near-optimal soft detection (SoD) algorithms based on HSD (SoD-HSD) with simulations.

Hard sphere-decoding (SD) has well appreciated merits for near-optimal demodulation of multiuser, block single-antenna, or, multiantenna transmissions over multiinput multioutput (MIMO) channels. At increased complexity, a soft version of SD, so termed list SD (LSD), has been recently applied to coded layered space-time (LST) systems enabling them to approach MIMO channel capacity. By introducing a novel bit-level multistream LST transmitter along with a soft-to-hard decoder conversion, we show how to achieve the near-capacity performance of LSD at reduced complexity, and even outperform it as the size of the block to be decoded (M) increases. Specifically, for binary real LST codes we develop exact max-log based SD schemes with average complexity O(M/sup 4/), and various approximate alternatives trading-off performance for average complexity down to O(M/sup 3/). These schemes apply directly to the real and imaginary parts of QPSK signalling, and also to QAM signalling after incorporating an appropriate interference estimation and cancellation module. We corroborate our reduced-complexity near-optimal soft SD algorithms with simulations.

Abstract A full‐diversity full‐rate (FDFR) multi‐antenna system was developed recently, enabling uncoded layered space‐time (LST) transmissions to achieve full‐diversity (Nt) and full‐rate (Ntsymbols per channel use) simultaneously, for any number of transmit antennasNtand receive antennasNr. In this paper, we investigate the performance of a coded FDFR design obtained by concatenating an error control coding (ECC) module and FDFR module with a random interleaver in between. Turbo decoding is performed at the receiver. WithRcdenoting the ECC rate,dminthe minimum Hamming distance of the ECC, andMthe constellation size, an overall transfer rate ofRcNtlog2Mbits per channel use and a full diversity orderdminNtNrare achieved. Different ECC choices are considered. Approximate analysis reveals that multi‐stream ECC and single‐stream ECC make no difference when convolutional codes with long frame length and near‐optimal MIMO decoding schemes are adopted. Without sacrificing rate, the coded FDFR system improves error performance compared with coded V‐BLAST, when relatively weak codes are used. AsNrincreases, even strong codes such as rate 1/2 turbo codes can benefit from FDFR. Specifically, 1.5–2 dB gain over coded V‐BLAST is obtained in a 2 × 2 antenna setup when convolutional codes or rate 3/4 turbo codes are used; 0.5 dB gain is offered in a 2 × 5 setup when rate 1/2 turbo codes are used. Coded FDFR also outperforms a 16‐QAM Alamouti coded scheme by 1 dB when convolutional codes are used. The price paid is increased complexity. Copyright © 2004 John Wiley & Sons, Ltd.