Trellis-Based Equalization for Sparse ISI Channels Revisited

Sparse intersymbol-interference (ISI) channels are encountered in a variety of high-data-rate communication systems. Such channels have a large channel memory length, but only a small number of significant channel coefficients. In this paper, trellis-based equalization of sparse ISI channels is revisited. Due to the large channel memory length, the complexity of maximum-likelihood detection, e.g., by means of the Viterbi algorithm (VA), is normally prohibitive. In the first part of the paper, a unified framework based on factor graphs is presented for complexity reduction without loss of optimality. In this new context, two known reduced-complexity algorithms for sparse ISI channels are recapitulated: The multi-trellis VA (M-VA) and the parallel-trellis VA (P-VA). It is shown that the M-VA, although claimed, does not lead to a reduced computational complexity. The P-VA, on the other hand, leads to a significant complexity reduction, but can only be applied for a certain class of sparse channels. In the second part of the paper, a unified approach is investigated to tackle general sparse channels: It is shown that the use of a linear filter at the receiver renders the application of standard reduced-state trellis-based equalizer algorithms feasible, without significant loss of optimality. Numerical results verify the efficiency of the proposed receiver structure.Comment: To be presented at the 2005 IEEE Int. Symp. Inform. Theory (ISIT 2005), September 4-9, 2005, Adelaide, Australi

Self-concatenated code design and its application in power-efficient cooperative communications

In this tutorial, we have focused on the design of binary self-concatenated coding schemes with the help of EXtrinsic Information Transfer (EXIT) charts and Union bound analysis. The design methodology of future iteratively decoded self-concatenated aided cooperative communication schemes is presented. In doing so, we will identify the most important milestones in the area of channel coding, concatenated coding schemes and cooperative communication systems till date and suggest future research directions

Blind Estimation of Linear and Nonlinear Sparse Channels, Journal of Telecommunications and Information Technology, 2013, nr 1

This paper presents a Clustering Based Blind Channel Estimator for a special case of sparse channels – the zero pad channels. The proposed algorithm uses an unsupervised clustering technique for the estimation of data clusters. Clusters labelling is performed by a Hidden Markov Model of the observation sequence appropriately modified to exploit channel sparsity. The algorithm achieves a substantial complexity reduction compared to the fully evaluated technique. The proposed algorithm is used in conjunction with a Parallel Trellis Viterbi Algorithm for data detection and simulation results show that the overall scheme exhibits the reduced complexity benefits without performance reduction

Integrated approach for efficient power consumption and resource allocation in MIMO-OFDMA

The growing interest towards wireless communication advancement with smart devices has provided the desired throughput of wireless communication mechanisms. But, attaining high-speed data packets amenities is the biggest issue in different multimedia applications. Recently, OFDM has come up with the useful features for wireless communication however it faces interference issues at carrier level (intercarrier interferences). To resolve these interference issues in OFDM, various existing mechanisms were utilized cyclic prefix, but it leads to redundancy in transmitted data. Also, the transmission of this redundant data can take some more power and bandwidth. All these limitations factors can be removed from a parallel cancellation mechanism. The integration of parallel cancellation and Convolution Viterbi encoding and decoding in MIMO-OFDMA will be an effective solution to have high data rate which also associations with the benefits of both the architectures of MIMO and OFDMA modulation approaches. This paper deals with this integrated mechanism for efficient resource allocation and power consumption. For performance analysis, MIMO-OFDMA system is analyzed with three different approaches likeMIMO-OFDM system without parallel cancellation (MIMO-OFDMA-WPC), MIMO-OFDMA System with parallel cancellation (MIMO-OFDMA-PC) and proposed IMO-OFDMA system with parallel cancellation and Convolution Viterbi encoding/decoding (pMIMO-OFDMA-PC &CVed) for 4x4 transmitter and receiver. Through performance analysis, it is found that the proposed system achieved better resource allocation (bandwidth) with high data rate by minimized BER rate and achieved least power consumption with least BER

Nested turbo codes for the costa problem

Driven by applications in data-hiding, MIMO broadcast channel coding, precoding for interference cancellation, and transmitter cooperation in wireless networks, Costa coding has lately become a very active research area. In this paper, we first offer code design guidelines in terms of source- channel coding for algebraic binning. We then address practical code design based on nested lattice codes and propose nested turbo codes using turbo-like trellis-coded quantization (TCQ) for source coding and turbo trellis-coded modulation (TTCM) for channel coding. Compared to TCQ, turbo-like TCQ offers structural similarity between the source and channel coding components, leading to more efficient nesting with TTCM and better source coding performance. Due to the difference in effective dimensionality between turbo-like TCQ and TTCM, there is a performance tradeoff between these two components when they are nested together, meaning that the performance of turbo-like TCQ worsens as the TTCM code becomes stronger and vice versa. Optimization of this performance tradeoff leads to our code design that outperforms existing TCQ/TCM and TCQ/TTCM constructions and exhibits a gap of 0.94, 1.42 and 2.65 dB to the Costa capacity at 2.0, 1.0, and 0.5 bits/sample, respectively

Sequence codes

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