Channel coded iterative center-shifting K-best sphere detection for rank-deficient systems

Based on an EXtrinsic Information Transfer (EXIT) chart assisted receiver design, a low-complexity near-Maximum A Posteriori (MAP) detector is constructed for high-throughput MIMO systems. A high throughput is achieved by invoking high-order modulation schemes and/or multiple transmit antennas, while employing a novel sphere detector (SD) termed as a center-shifting SD scheme, which updates the SD’s search center during its consecutive iterations with the aid of channel decoder. Two low-complexity iterative center-shifting SD aided receiver architectures are investigated, namely the direct-hard-decision centershifting (DHDC) and the direct-soft-decision center-shifting (DSDC) schemes. Both of them are capable of attaining a considerable memory and complexity reduction over the conventional SD-aided iterative benchmark receiver. For example, the DSDC scheme reduces the candidate-list-generation-related and extrinsic-LLR-calculation related complexity by a factor of 3.5 and 16, respectively. As a further benefit, the associated memory requirements were also reduced by a factor of 16

Iterative amplitude/phase multiple-symbol differential sphere detection for DAPSK modulated transmissions

Differentially encoded and non-coherently detected transceivers exhibit a low complexity, since they dispense with complex channel estimation. Albeit this is achieved at the cost of requiring an increased transmit power, they are particularly beneficial, for example in cooperative communication scenarios, where the employment of channel estimation for all the mobile-to-mobile links may become unrealistic. In pursuit of high bandwidth efficiency, differential amplitude and phase shift keying (DAPSK) was devised using constellations of multiple concentric rings. In order to increase resilience against the typical high-Doppler-induced performance degradation of DAPSK and/or enhance the maximum achievable error-free transmission rate for DAPSK modulated systems, multiple-symbol differential detection (MSDD) may be invoked. However, the complexity of the maximum-a-posteriori (MAP) MSDD increases exponentially with the detection window size and hence may become excessive upon increasing the window size, especially in the context of iterative detection aided channel coded system. In order to circumvent this excessive complexity, we conceive a decomposed two-stage iterative amplitude and phase (A/P) detection framework, where the challenge of having a non-constant-modulus constellation is tackled with the aid of a specifically designed information exchange between the independent A/P detection stages, thus allowing the incorporation of reduced-complexity sphere detection (SD). Consequently, a near-MAP-MSDD performance can be achieved at a significantly reduced complexity, which may be five orders of magnitude lower than that imposed by the traditional MAP-MSDD in the 16-DAPSK scenario considered

Adaptive and Iterative Multi-Branch MMSE Decision Feedback Detection Algorithms for MIMO Systems

In this work, decision feedback (DF) detection algorithms based on multiple processing branches for multi-input multi-output (MIMO) spatial multiplexing systems are proposed. The proposed detector employs multiple cancellation branches with receive filters that are obtained from a common matrix inverse and achieves a performance close to the maximum likelihood detector (MLD). Constrained minimum mean-squared error (MMSE) receive filters designed with constraints on the shape and magnitude of the feedback filters for the multi-branch MMSE DF (MB-MMSE-DF) receivers are presented. An adaptive implementation of the proposed MB-MMSE-DF detector is developed along with a recursive least squares-type algorithm for estimating the parameters of the receive filters when the channel is time-varying. A soft-output version of the MB-MMSE-DF detector is also proposed as a component of an iterative detection and decoding receiver structure. A computational complexity analysis shows that the MB-MMSE-DF detector does not require a significant additional complexity over the conventional MMSE-DF detector, whereas a diversity analysis discusses the diversity order achieved by the MB-MMSE-DF detector. Simulation results show that the MB-MMSE-DF detector achieves a performance superior to existing suboptimal detectors and close to the MLD, while requiring significantly lower complexity.Comment: 10 figures, 3 tables; IEEE Transactions on Wireless Communications, 201

MIMO-aided near-capacity turbo transceivers: taxonomy and performance versus complexity

In this treatise, we firstly review the associated Multiple-Input Multiple-Output (MIMO) system theory and review the family of hard-decision and soft-decision based detection algorithms in the context of Spatial Division Multiplexing (SDM) systems. Our discussions culminate in the introduction of a range of powerful novel MIMO detectors, such as for example Markov Chain assisted Minimum Bit-Error Rate (MC-MBER) detectors, which are capable of reliably operating in the challenging high-importance rank-deficient scenarios, where there are more transmitters than receivers and hence the resultant channel-matrix becomes non-invertible. As a result, conventional detectors would exhibit a high residual error floor. We then invoke the Soft-Input Soft-Output (SISO) MIMO detectors for creating turbo-detected two- or three-stage concatenated SDM schemes and investigate their attainable performance in the light of their computational complexity. Finally, we introduce the powerful design tools of EXtrinsic Information Transfer (EXIT)-charts and characterize the achievable performance of the diverse near- capacity SISO detectors with the aid of EXIT charts