A Low-Complexity, Full-Rate, Full-Diversity 2 X 2 STBC with Golden Code's Coding Gain

This paper presents a low-ML-decoding-complexity, full-rate, full-diversity space-time block code (STBC) for a 2 transmit antenna, 2 receive antenna multiple-input multiple-output (MIMO) system, with coding gain equal to that of the best and well known Golden code for any QAM constellation. Recently, two codes have been proposed (by Paredes, Gershman and Alkhansari and by Sezginer and Sari), which enjoy a lower decoding complexity relative to the Golden code, but have lesser coding gain. The $2\times 2$ STBC presented in this paper has lesser decoding complexity for non-square QAM constellations, compared with that of the Golden code, while having the same decoding complexity for square QAM constellations. Compared with the Paredes-Gershman-Alkhansari and Sezginer-Sari codes, the proposed code has the same decoding complexity for non-rectangular QAM constellations. Simulation results, which compare the codeword error rate (CER) performance, are presented.Comment: Submitted to IEEE Globecom - 2008. 6 pages, 3 figures, 1 tabl

Deep learning-based space-time coding wireless MIMO receiver optimization.

Doctoral Degree. University of KwaZulu-Natal, Durban.With the high demand for high data throughput and reliable wireless links to cater for real-time or low latency mobile application services, the wireless research community has developed wireless multiple-input multiple-output (MIMO) architectures that cater to these stringent quality of service (QoS) requirements. For the case of wireless link reliability, spatial diversity in wireless MIMO architectures is used to increase the link reliability. Besides increasing link reliability using spatial diversity, space-time block coding schemes may be used to further increase the wireless link reliability by adding time diversity to the wireless link. Our research is centered around the optimization of resources used in decoding space-time block coded wireless signals. There are two categories of space-time block coding schemes namely the orthogonal and non-orthogonal space-time block codes (STBC). In our research, we concentrate on two non-orthogonal STBC schemes namely the uncoded space-time labeling diversity (USTLD) and the Golden code. These two non-orthogonal STBC schemes exhibit some advantages over the orthogonal STBC called Alamouti despite their non-linear optimal detection. Orthogonal STBC schemes have the advantage of simple linear optimal detection relative to the more complex non-linear optimal detection of non-orthogonal STBC schemes. Since our research concentrates on wireless MIMO STBC transmission, for detection to occur optimally at the receiver side of a space-time block coded wireless MIMO link, we need to optimally perform channel estimation and decoding. USTLD has a coding gain advantage over the Alamouti STBC scheme. This implies that the USTLD can deliver higher wireless link reliability relative to the Alamouti STBC for the same spectral efficiency. Despite this advantage of the USTLD, to the best of our knowledge, the literature has concentrated on USTLD wireless transmission under the assumption that the wireless receiver has full knowledge of the wireless channel without estimation errors. We thus perform research of the USTLD wireless MIMO transmission with imperfect channel estimation. The traditional least-squares (LS) and minimum mean squared error (MMSE) used in literature, for imperfect pilot-assisted channel estimation, require the full knowledge of the transmitted pilot symbols and/or wireless channel second order statistics which may not always be fully known. We, therefore, propose blind channel estimation facilitated by a deep learning model that makes it unnecessary to have prior knowledge of the wireless channel second order statistics, transmitted pilot symbols and/or average noise power. We also derive an optimal number of pilot symbols that maybe used for USTLD wireless MIMO channel estimation without compromising the wireless link reliability. It is shown from the Monte Carlo simulations that the error rate performance of the USTLD transmission is not compromised despite using only 20% of the required number of Zadoff-Chu sequence pilot symbols used by the traditional LS and MMSE channel estimators for both 16-QAM and 16-PSK baseband modulation. The Golden code is a STBC scheme with spatial multiplexing gain over the Alamouti scheme. This implies that the Golden code can deliver higher spectral efficiencies for the same link reliability with the Alamouti scheme. The Alamouti scheme has been implemented in the modern wireless standards because it adds time diversity, with low decoding complexity, to wireless MIMO links. The Golden code adds time diversity and improves wireless MIMO spectral efficiency but at the cost of much higher decoding complexity relative to the Alamouti scheme. Because of the high decoding complexity, the Golden code is not widely adopted in the modern wireless standards. We, therefore, propose analytical and deep learning-based sphere-decoding algorithms to lower the number of detection floating-point operations (FLOPS) and decoding latency of the Golden code under low- and high-density M-ary quadrature amplitude modulation (M-QAM) baseband transmissions whilst maintaining the near-optimal error rate performance. The proposed sphere-decoding algorithms achieve at most 99% reduction in Golden code detection FLOPS, at low SNR, relative to the sphere-decoder with sorted detection subsets (SD-SDS) whilst maintaining the error rate performance. For the case of high-density M-QAM Golden code transmission, the proposed analytical and deep learning sphere-decoders reduce decoding latency by at most 70%, relative to the SD-SDS decoder, without diminishing the error rate performance

Super-orthogonal space-time turbo codes in Rayleigh fading channels.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, 2005.The vision of anytime, anywhere communications coupled by the rapid growth of wireless subscribers and increased volumes of internet users, suggests that the widespread demand for always-on access data, is sure to be a major driver for the wireless industry in the years to come. Among many cutting edge wireless technologies, a new class of transmission techniques, known as Multiple-Input Multiple-Output (MIMO) techniques, has emerged as an important technology leading to promising link capacity gains of several fold increase in data rates and spectral efficiency. While the use of MIMO techniques in the third generation (3G) standards is minimal, it is anticipated that these technologies will play an important role in the physical layer of fixed and fourth generation (4G) wireless systems. Concatenated codes, a class of forward error correction codes, of which Turbo codes are a classical example, have been shown to achieve reliable performance which approach the Shannon limit. An effective and practical way to approach the capacity of MIMO wireless channels is to employ space-time coding (STC). Space-Time coding is based on introducing joint correlation in transmitted signals in both the space and time domains. Space-Time Trellis Codes (STTCs) have been shown to provide the best trade-off in terms of coding gain advantage, improved data rates and computational complexity. Super-Orthogonal Space-Time Trellis Coding (SOSTTC) is the recently proposed form of space-time trellis coding which outperforms its predecessor. The code has a systematic design method to maximize the coding gain for a given rate, constellation size, and number of states. Simulation and analytical results are provided to justify the improved performance. The main focus of this dissertation is on STTCs, SOSTTCs and their concatenated versions in quasi-static and rapid Rayleigh fading channels. Turbo codes and space-time codes have made significant impact in terms of the theory and practice by closing the gap on the Shannon limit and the large capacity gains provided by the MIMO channel, respectively. However, a convincing solution to exploit the capabilities provided by a MIMO channel would be to build the turbo processing principle into the design of MIMO architectures. The field of concatenated STTCs has already received much attention and has shown improved performance over conventional STTCs. Recently simple and double concatenated STTCs structures have shown to provide a further improvement performance. Motivated by this fact, two concatenated SOSTTC structures are proposed called Super-orthogonal space-time turbo codes. The performance of these new concatenated SOSTTC is compared with that of concatenated STTCs and conventional SOSTTCs with simulations in Rayleigh fading channels. It is seen that the SOST-CC system outperforms the ST-CC system in rapid fading channels, whereas it maintains performance similar to that in quasi-static. The SOST-SC system has improved performance for larger frame lengths and overall maintains similar performance with ST-SC systems. A further investigation of these codes with channel estimation errors is also provided

A Low-Complexity, Full-Rate, Full-Diversity 2 x 2 STBC with Golden Code's Coding Gain

This paper presents a low-ML-decoding-complexity, full-rate, full-diversity space-time block code (STBC) for a 2 transmit antenna, 2 receive antenna multiple-input multiple-output (MIMO) system, with coding gain equal to that of the best and well known Golden code for any QAM constellation. Recently, two codes have been proposed (by Paredes, Gershman and Alkhansari and by Sezginer and Sari), which enjoy a lower decoding complexity relative to the Golden code, but have lesser coding gain. The 2 x 2 STBC presented in this paper has lesser decoding complexity for non-square QAM constellations, compared with that of the Golden code, while having the same decoding complexity for square QAM constellations. Compared with the Paredes-Gershman-Alkhansari and Sezginer-Sari codes, the proposed code has the same decoding complexity for non-rectangular QAM constellations. Simulation results, which compare the codeword error rate (CER) performance, are presented