Generalized feedback detection for spatial multiplexing multi-antenna systems

We present a unified detection framework for spatial multiplexing multiple-input multiple-output (MIMO) systems by generalizing Heller’s classical feedback decoding algorithm for convolutional codes. The resulting generalized feedback detector (GFD) is characterized by three parameters: window size, step size and branch factor. Many existing MIMO detectors are turned out to be special cases of the GFD. Moreover, different parameter choices can provide various performance-complexity tradeoffs. The connection between MIMO detectors and tree search algorithms is also established. To reduce redundant computations in the GFD, a shared computation technique is proposed by using a tree data structure. Using a union bound based analysis of the symbol error rates, the diversity order and signal-to-noise ratio (SNR) gain are derived analytically as functions of the three parameters; for example, the diversity order of the GFD varies between 1 and N. The complexity of the GFD varies between those of the maximum-likelihood (ML) detector and the zero-forcing decision feedback detector (ZFDFD). Extensive computer simulation results are also provided

Joint data detection and channel estimation for OFDM systems

We develop new blind and semi-blind data detectors and channel estimators for orthogonal frequency-division multiplexing (OFDM) systems. Our data detectors require minimizing a complex, integer quadratic form in the data vector. The semi-blind detector uses both channel correlation and noise variance. The quadratic for the blind detector suffers from rank deficiency; for this, we give a low-complexity solution. Avoiding a computationally prohibitive exhaustive search, we solve our data detectors using sphere decoding (SD) and V-BLAST and provide simple adaptations of the SD algorithm. We consider how the blind detector performs under mismatch, generalize the basic data detectors to nonunitary constellations, and extend them to systems with pilots and virtual carriers. Simulations show that our data detectors perform well

Transmission and detection for space-time block coding and v-blast systems

This dissertation focuses on topics of data transmission and detection of space -time block codes (STBC). The STBCs can be divided into two main categories, namely, the orthogonal space-time block codes (OSTBC) and the quasi-orthogonal space-time codes (Q-OSTBC). The space-time block coded systems from transceiver design perspective for both narrow-band and frequency selective wireless environment are studied. The dissertation also processes and studies a fast iterative detection scheme for a high-rate space-time transmission system, the V-BLAST system. In Chapter 2, a new OSTBC scheme with full-rate and full-diversity, which can be used on QPSK transceiver systems with four transmit antennas and any number of receivers is studied. The newly proposed coding scheme is a non-linear coding. Compared with full-diversity QOSTBC, an obvious advantage of our proposed new OSTBC is that the coded signals transmitted through all four transmit antennas do not experience any constellation expansion. In Chapter 3, a new fast coherent detection algorithm is proposed to provide maximum likelihood (ML) detection for Q-OSTBC. The new detection scheme is also very useful to analysis the diversity property of Q-OSTBC and design full diversity Q-OSTBC codes. The complexity of the new proposed detection algorithm can be independent to the modulation order and is especially suitable for high data rate transmission. In Chapter 4, the space-time coding schemes in frequency selective channels are studied. Q-OSTC transmission and detection schemes are firstly extended for frequency selective wireless environment. A new block based quasi-orthogonal space-time block encoding and decoding (Q-OSTBC) scheme for a wireless system with four transmit antennas is proposed in frequency selective fading channels. The proposed MLSE detection scheme effectively combats channel dispersion and frequency selectivity due to multipath, yet still provides full diversity gain. However, since the computational complexity of MLSE detection increases exponentially with the maximum delay of the frequency selective channel, a fast sub-optimal detection scheme using MMSE equalizer is also proposed, especially for channels with large delays. The Chapter 5 focuses on the V-BLAST system, an important high-rate space-time data transmission scheme. A reduced complexity ML detection scheme for VBLAST systems, which uses a pre-decoder guided local exhaustive search is proposed and studied. A polygon searching algorithm and an ordered successive interference cancellation (O-SIC) sphere searching algorithm are major components of the proposed multi-step ML detectors. At reasonable high SNRs, our algorithms have low complexity comparable to that of O-SIC algorithm, while they provide significant performance improvement. Another new low complexity algorithm termed ordered group-wise interference cancellation (O-GIC) is also proposed for the detection of high dimensional V-BLAST systems. The O-GIC based detection scheme is a sub-optimal detection scheme, however, it outperforms the O-SIC

Statistical Pruning for Near Maximum Likelihood Detection of MIMO Systems

We show a statistical pruning approach for maximum likelihood (ML) detection of multiple-input multiple-output (MIMO) systems. We present a general pruning strategy for sphere decoder (SD), which can also be applied to any tree search algorithms. Our pruning rules are effective especially for the case when SD has high complexity. Three specific pruning rules are given and discussed. From analyzing the union bound on the symbol error probability, we show that the diversity order of the deterministic pruning is only one by fixing the pruning probability. By choosing different pruning probability distribution functions, the statistical pruning can achieve arbitrary diversity orders and SNR gains. Our statistical pruning strategy thus achieves a flexible trade-off between complexity and performance

Blind Receiver Design for OFDM Systems Over Doubly Selective Channels

We develop blind data detectors for orthogonal frequency-division multiplexing (OFDM) systems over doubly selective channels by exploiting both frequency-domain and time-domain correlations of the received signal. We thus derive two blind data detectors: a time-domain data detector and a frequency-domain data detector. We also contribute a reduced complexity, suboptimal version of a time-domain data detector that performs robustly when the normalized Doppler rate is less than 3%. Our frequency-domain data detector and suboptimal time-domain data detector both result in integer least-squares (LS) problems. We propose the use of the V-BLAST detector and the sphere decoder. The time-domain data detector is not limited to the Doppler rates less than 3%, but cannot be posed as an integer LS problem. Our solution is to develop an iterative algorithm that starts from the suboptimal time-domain data detector output. We also propose channel estimation and prediction algorithms using a polynomial expansion model, and these estimators work with data detectors (decision-directed mode) to reduce the complexity. The estimators for the channel statistics and the noise variance are derived using the likelihood function for the data. Our blind data detectors are fairly robust against the parameter mismatch

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

High-Rate Space-Time Coded Large MIMO Systems: Low-Complexity Detection and Channel Estimation

In this paper, we present a low-complexity algorithm for detection in high-rate, non-orthogonal space-time block coded (STBC) large-MIMO systems that achieve high spectral efficiencies of the order of tens of bps/Hz. We also present a training-based iterative detection/channel estimation scheme for such large STBC MIMO systems. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed multistage likelihood ascent search (M-LAS) detector in conjunction with the proposed iterative detection/channel estimation scheme at low complexities. The fact that we could show such good results for large STBCs like 16x16 and 32x32 STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot based training for channel estimation and turbo coding) establishes the effectiveness of the proposed detector and channel estimator. We decode perfect codes of large dimensions using the proposed detector. With the feasibility of such a low-complexity detection/channel estimation scheme, large-MIMO systems with tens of antennas operating at several tens of bps/Hz spectral efficiencies can become practical, enabling interesting high data rate wireless applications.Comment: v3: Performance/complexity comparison of the proposed scheme with other large-MIMO architectures/detectors has been added (Sec. IV-D). The paper has been accepted for publication in IEEE Journal of Selected Topics in Signal Processing (JSTSP): Spl. Iss. on Managing Complexity in Multiuser MIMO Systems. v2: Section V on Channel Estimation is update