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.

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.

Abstract-Closest point algorithms find wide applications in decoding block transmissions encountered with single- or multiuser communication links relying on a single or multiple antennas. Capitalizing on the random channel and noise models typically encountered in wireless communications, the sphere decoding algorithm (SDA) and related complexity-reducing techniques are approached in this paper from a probabilistic perspective. With both theoretical analysis and simulations, combining SDA with detection ordering is justified. A novel probabilistic search algorithm examining potential candidates in a descending probability order is derived and analyzed. Based on probabilistic search and an error-performance-oriented fast stopping criterion, a computationally efficient layered search is developed. Having comparable decoding complexity to the nulling-canceling (NQ algorithm with detection ordering, simulations confirm that the novel layered search achieves considerable error-performance enhancement.

We start by identifying a relatively efficient version of sphere decoding algorithm (SDA) that performs exact maximum-likelihood (ML) decoding. We develop novel algorithms based on an improved increasing radius search (IIRS), which offer error performance and decoding complexity between two extremes: the ML receiver and the nulling-canceling (NC) receiver with detection ordering. With appropriate choices of parameters, our IIRS offers the flexibility to trade error performance for complexity. We provide design intuitions and guidelines, analytical parameter specifications, and a semianalytical error-performance analysis. Simulations illustrate that IIRS achieves considerable complexity reduction, while maintaining performance close to ML.

Layered space-time (LST) transmissions employing continuous phase modulations (CPM) are well motivated for both bandwidth- and power-limited multiantenna communications. However, one of the major challenges for LST-CPM is the high complexity it incurs with maximum likelihood (ML) detection. In this paper, we develop reduced complexity LST-CPM receivers. First, we consider single antenna systems. Specifically, we study a reduced complexity Viterbi receiver for binary CPM. Based on this design, we introduce differential encoding for a class of CPM signals and analyze its performance gain both theoretically and with simulations. Second, we focus on multiantenna LST systems with minimum shift-keying (MSK)-type modulations. With group nulling-canceling (NC) and low-complexity linear equalization, we convert a coded multiuser detection problem into an uncoded one with small equalization loss. We also find that the combination of sphere decoding with hard-decision iterative processing is effective in boosting performance with a controllable complexity increase. Both analytical and simulated performance confirm that the novel LST-MSK receiver exhibits markedly improved performance relative to conventional NC detectors with moderate complexity increase.

This work first identifies the most efficient version of the sphere decoding algorithms (SDA) We then develop a novel SDA based on an improved increasing radius search (IIRS), which essentially achieves maximum likelihood (ML) error performance with considerable complexity reduction and provides both design intuition and analytical parameter specification. A probabilistic trimming approach, which exploits both channel realizations and the noise distribution is also introduced. Simulations confirm our claims on both the IIRS and the probabilistic trimming aspects.

Frequency-shift keying (FSK) is a popular modulation scheme in power-limited communication links. This paper introduces space-time FSK (ST-FSK), which does not require any channel state information at the transmitter and the receiver, as in conventional noncoherent FSK. ST-FSK can be viewed as a special unitary ST modulation design. However, ST-FSK has a number of advantages over existing unitary ST modulation designs. ST-FSK is easier to design, and enjoys lower decoding complexity. Furthermore, ST-FSK guarantees full diversity. Finally, ST-FSK can be adopted in the digital as well as in the analog domain, and merges very naturally with frequency-hopping multiple access. As expected, all these advantages come at the cost of a decrease in spectral efficiency.

We construct unitary noncoherent space-time constellations, which can be considered as a concatenation of a training block with an orthogonal design. With a simple construction, our constellations are easy to design, enjoy full antenna diversity, allow for a simplified maximum-likelihood (ML) detector, and achieve error performance comparable to existing designs that rely on computer search. To exploit the constellation structures and improve coding gains, we further pursue a trellis-coded modulation (TCM) approach. Based on the sequence pairwise error analysis, we identify two simple parameters to quantify the asymptotic error performance, which enables us to compare among different TCM schemes or uncoded alternatives.

We design constellations for non-coherent space-time systems. Given in algebraic form, the constructed constellations are easy to design, enjoy full diversity, allow for a simplified maximum likelihood detector, and achieve performance comparable to existing designs that rely on computer search.