Improved OSIC decoder for spatially multiplexed system

Abstract

This paper proposes to use candidate symbol table for the decoding of the first few substreams for spatially multiplexed system. In the new decoding algorithm, we generate candidate symbol table (CST) and do ordered successive interference cancellation (OSIC) for each candidates. At the end, Maximum Likelihood (ML) criteria is used to determine the optimum transmit symbol vector among the estimated candidates. Simulation result shows that the size of CST can be maintained to be small, even if the number of bits per symbol increases. Simulation results show that this algorithm gives us performance close to ML decoder, and outperforms maximum likelihood decision feedback equalizer (ML-DFE) and channel-based adaptive group detection based OSIC (AGD-OSIC).

A Hybrid MMSE and K-Best Detection Scheme for MIMO Systems

“…The OSIC This work was supported by the National Science Council of Taiwan under Grant NSC 100-2221-E-001-004. scheme [11] detects symbols in descending order of their post-detection signal-to-noise ratio (SNR). The contribution of a detected symbol is then subtracted from the received signal before detecting the next symbol.…”

A New Multistage Whitener-Based Detector for MIMO Systems

“…Many studies have been conducted on MIMO decoding to reduce the computational complexity of the optimal MLD [3][4][5][6][7]. Among these detectors, Li et al suggested that a whitener [8] could be used as a suboptimal method for space-time coded MIMO orthogonal frequency division multiplexing (OFDM) with four transmit antennas [3].…”

An Efficient Soft-Output MIMO Detection Method Based on a Multiple-Channel-Ordering Technique

“…As a result, most recent works have focused on the detection methods that are based on tree searches, which achieve nearoptimal performance but involve significantly less complexity than the original ML method [17]. These methods, however, cannot provide the best solution for soft-decoding MIMO systems because of the empty set problem [12], [13].…”

“…While most of recent detection methods are based on the tree search algorithm [3]- [15], this paper proposes an efficient detection method that is based on the OSIC algorithm. The performance of the original OSIC method itself is usually unacceptable for actual use, and there have been several attempts to enhance the original OSIC algorithm [16], [17]. These methods, however, cannot provide the best solution for soft-decoding MIMO systems because of the empty set problem [12], [13].…”

“…The ordered successive interference cancellation (OSIC) algorithm reduces the effect of interference signals by eliminating signals that are already detected [2]. Although the OSIC algorithm performs better than linear detection methods, it suffers from the error propagation problem [1], [2].As a result, most recent works have focused on the detection methods that are based on tree searches, which achieve nearoptimal performance but involve significantly less complexity than the original ML method [17]. These methods, however, cannot provide the best solution for soft-decoding MIMO systems because of the empty set problem [12], [13].…”