An Iterative Soft Decision Based LR-Aided MIMO Detector

The demand for wireless and high-rate communication system is increasing gradually and multiple-input-multiple-output (MIMO) is one of the feasible solutions to accommodate the growing demand for its spatial multiplexing and diversity gain. However, with high number of antennas, the computational and hardware complexity of MIMO increases exponentially. This accumulating complexity is a paramount problem in MIMO detection system directly leading to large power consumption. Hence, the major focus of this dissertation is algorithmic and hardware development of MIMO decoder with reduced complexity for both real and complex domain, which can be a beneficial solution with power efficiency and high throughput. Both hard and soft domain MIMO detectors are considered. The use of lattice reduction (LR) algorithm and on-demand-child-expansion for the reduction of noise propagation and node calculation respectively are the two of the key features of our developed architecture, presented in this literature. The real domain iterative soft MIMO decoding algorithm, simulated for 4 × 4 MIMO with different modulation scheme, achieves 1.1 to 2.7 dB improvement over Lease Sphere Decoder (LSD) and more than 8x reduction in list size, K as well as complexity of the detector. Next, the iterative real domain K-Best decoder is expanded to the complex domain with new detection scheme. It attains 6.9 to 8.0 dB improvement over real domain K-Best decoder and 1.4 to 2.5 dB better performance over conventional complex decoder for 8 × 8 MIMO with 64 QAM modulation scheme. Besides K, a new adjustable parameter, Rlimit has been introduced in order to append re-configurability trading-off between complexity and performance. After that, a novel low-power hardware architecture of complex decoder is developed for 8 × 8 MIMO and 64 QAM modulation scheme. The total word length of only 16 bits has been adopted limiting the bit error rate (BER) degradation to 0.3 dB with K and Rlimit equal to 4. The proposed VLSI architecture is modeled in Verilog HDL using Xilinx and synthesized using Synopsys Design Vision in 45 nm CMOS technology. According to the synthesize result, it achieves 1090.8 Mbps throughput with power consumption of 580 mW and latency of 0.33 us. The maximum frequency the design proposed is 181.8 MHz. All of the proposed decoders mentioned above are bounded by the fixed K. Hence, an adaptive real domain K-Best decoder is further developed to achieve the similar performance with less K, thereby reducing the computational complexity of the decoder. It does not require accurate SNR measurement to perform the initial estimation of list size, K. Instead, the difference between the first two minimal distances is considered, which inherently eliminates complexity. In summary, a novel iterative K-Best detector for both real and complex domain with efficient VLSI design is proposed in this dissertation. The results from extensive simulation and VHDL with analysis using Synopsys tool are also presented for justification and validation of the proposed works

An Iterative Soft Decision Based LR-Aided MIMO Detector

The demand for wireless and high-rate communication system is increasing gradually and multiple-input-multiple-output (MIMO) is one of the feasible solutions to accommodate the growing demand for its spatial multiplexing and diversity gain. However, with high number of antennas, the computational and hardware complexity of MIMO increases exponentially. This accumulating complexity is a paramount problem in MIMO detection system directly leading to large power consumption. Hence, the major focus of this dissertation is algorithmic and hardware development of MIMO decoder with reduced complexity for both real and complex domain, which can be a beneficial solution with power efficiency and high throughput. Both hard and soft domain MIMO detectors are considered. The use of lattice reduction (LR) algorithm and on-demand-child-expansion for the reduction of noise propagation and node calculation respectively are the two of the key features of our developed architecture, presented in this literature. The real domain iterative soft MIMO decoding algorithm, simulated for 4 × 4 MIMO with different modulation scheme, achieves 1.1 to 2.7 dB improvement over Lease Sphere Decoder (LSD) and more than 8x reduction in list size, K as well as complexity of the detector. Next, the iterative real domain K-Best decoder is expanded to the complex domain with new detection scheme. It attains 6.9 to 8.0 dB improvement over real domain K-Best decoder and 1.4 to 2.5 dB better performance over conventional complex decoder for 8 × 8 MIMO with 64 QAM modulation scheme. Besides K, a new adjustable parameter, Rlimit has been introduced in order to append re-configurability trading-off between complexity and performance. After that, a novel low-power hardware architecture of complex decoder is developed for 8 × 8 MIMO and 64 QAM modulation scheme. The total word length of only 16 bits has been adopted limiting the bit error rate (BER) degradation to 0.3 dB with K and Rlimit equal to 4. The proposed VLSI architecture is modeled in Verilog HDL using Xilinx and synthesized using Synopsys Design Vision in 45 nm CMOS technology. According to the synthesize result, it achieves 1090.8 Mbps throughput with power consumption of 580 mW and latency of 0.33 us. The maximum frequency the design proposed is 181.8 MHz. All of the proposed decoders mentioned above are bounded by the fixed K. Hence, an adaptive real domain K-Best decoder is further developed to achieve the similar performance with less K, thereby reducing the computational complexity of the decoder. It does not require accurate SNR measurement to perform the initial estimation of list size, K. Instead, the difference between the first two minimal distances is considered, which inherently eliminates complexity. In summary, a novel iterative K-Best detector for both real and complex domain with efficient VLSI design is proposed in this dissertation. The results from extensive simulation and VHDL with analysis using Synopsys tool are also presented for justification and validation of the proposed works

FlexCore: Massively Parallel and Flexible Processing for Large MIMO Access Points

Large MIMO base stations remain among wireless network designers’ best tools for increasing wireless throughput while serving many clients, but current system designs, sacrifice throughput with simple linear MIMO detection algorithms. Higher-performance detection techniques are known, but remain off the table because these systems parallelize their computation at the level of a whole OFDM subcarrier, sufficing only for the less demanding linear detection approaches they opt for. This paper presents FlexCore, the first computational architecture capable of parallelizing the detection of large numbers of mutually-interfering information streams at a granularity below individual OFDM subcarriers, in a nearly-embarrassingly parallel manner while utilizing any number of available processing elements. For 12 clients sending 64-QAM symbols to a 12-antenna base station, our WARP testbed evaluation shows similar network throughput to the state-of-the-art while using an order of magnitude fewer processing elements. For the same scenario, our combined WARP-GPU testbed evaluation demonstrates a 19x computational speedup, with 97% increased energy efficiency when compared with the state of the art. Finally, for the same scenario, an FPGA-based comparison between FlexCore and the state of the art shows that FlexCore can achieve up to 96% better energy efficiency, and can offer up to 32x the processing throughput

A High Throughput Configurable SDR Detector for Multi-user MIMO Wireless Systems

Spatial division multiplexing (SDM) in MIMO technology significantly increases the spectral efficiency, and hence capacity, of a wireless communication system: it is a core component of the next generation wireless systems, e.g. WiMAX, 3GPP LTE and other OFDM-based communication schemes. Moreover, spatial division multiple access (SDMA) is one of the widely used techniques for sharing the wireless medium between different mobile devices. Sphere detection is a prominent method of simplifying the detection complexity in both SDM and SDMA systems while maintaining BER performance comparable with the optimum maximum-likelihood (ML) detection. On the other hand, with different standards supporting different system parameters, it is crucial for both base station and handset devices to be configurable and seamlessly switch between different modes without the need for separate dedicated hardware units. This challenge emphasizes the need for SDR designs that target the handset devices. In this paper, we propose the architecture and FPGA realization of a configurable sort-free sphere detector, Flex-Sphere, that supports 4, 16, 64-QAM modulations as well as a combination of 2, 3 and 4 antenna/user configuration for handsets. The detector provides a data rate of up to 857.1 Mbps that fits well within the requirements of any of the next generation wireless standards. The algorithmic optimizations employed to produce an FPGA friendly realization are discussed.Xilinx Inc.National Science Foundatio

Detection and decoding algorithms of multi-antenna diversity techniques for terrestrial DVB systems

This PhD dissertation analyzes the behavior of multi-antenna diversity techniques in broadcasting scenarios of TDT (terrestrial digital television) systems and proposes a low-complexity detection and decoding design for their practical implementation. For that purpose, the transmission-reception chains of the European DVB-T (Digital Video Broadcasting - Terrestrial) and DVB-T2 standards have been implemented over which diversity and MIMO (multiple-input multiple-output) techniques have been assessed through Monte Carlo simulations. On one hand, the most important multi-antenna diversity techniques such as CDD (cyclic delay diversity), Alamouti code-based SFBC (space-frequency block coding) and MRC (maximum ratio combining), have been evaluated in a DVB-T system over both fixed and mobile Rayleigh and Ricean channels. With the DVB-T2 standard release, multi-antenna processing has actually been introduced in digital television systems. The distributed SFBC configuration proposed in DVB-T2 is analyzed from a performance point of view considering different propagation conditions in an SFN (single frequency network). On the other hand, error-performance and detection complexity analyses of 2x2 FRFD (full-rate full-diversity) SFBCs are carried out for last-generation DTV (digital television) systems. The use of channel coding based on LDPC (low-density parity check) codes in new standards such as DVB-T2, involves a soft-output MAP (maximum a posteriori ) detection which results in an increase of the detection complexity. In order to study the FRFD codes behavior in such a BICM (bit-interleaved coded modulation) scheme, the Golden code, which achieves the maximum coding gain, and the Sezginer-Sari code, which has a lower inherent detection complexity as an expense of sacrificing performance gain, have been chosen. Using LSD (list sphere decoder) detection, BER (bit error rate) performance and computational cost results are provided for TDT scenarios. In order to overcome the variable complexity of the LSD, LFSD (list fixed-complexity sphere decoder) detection is proposed for practical implementations. A redesign of the previously proposed LFSD algorithm for spatial multiplexing MIMO systems has been performed for FRFD SFBCs with close-to-LSD performance. Furthermore, an analysis of the number of candidates is carried out in order to maximize the eficiency of the algorithm. Due to its fixed complexity, the novel algorithm can be fully pipelined making feasible a realistic implementation in chip.Esta tesis analiza el comportamiento de las técnicas de diversidad multiantena en escenarios de radiodifusión TDT (televisión digital terrestre) y propone un diseño de baja complejidad para la detección de códigos SFBC (space-frequency block coding ) que facilita una posible implementación práctica. Para ello, se ha implementado la cadena de transmisión-recepción de los estándares europeos DVB-T (Digital Video Broadcasting - Terrestrial ) y DVB-T2 como entorno de trabajo donde se han incluido y simulado diferentes técnicas de diversidad MIMO (multiple-input multiple-output ). Por un lado, se evalúan las técnicas de diversidad multiantena CDD ( cyclic delay diversity), SFBC con codi cación Alamouti y MRC (maximum ratio combining ) en escenarios fijos y móviles de canales tanto Rayleigh como Ricean para el sistema DVB-T. En DVB-T2, se analiza la tecnología multiantena propuesta por el estándar para diferentes escenarios de propagación dentro de redes SFN (single frequency network ). Por otro lado, se realiza un estudio sobre códigos FRFD (full-rate full-diversity ) SFBC para su posible inclusión en futuros estándares de televisión digital. El uso de codificaciones de canal más potentes, como los códigos LDPC (low-density parity check ), implica la utilización de una detección MAP (maximum a posteriori ) con salida soft, incrementando considerablemente la complejidad de la detección. Para realizar el correspondiente análisis de complejidad y rendimiento, se han escogidos dos códigos FRFD. Por un lado, el código Golden, que ofrece la máxima ganancia de código y, por otro, el código propuesto por Sezginer y Sari, que consigue reducir la complejidad de detección a costa de perder cierta ganancia de código. Se presentan resultados basados en curvas de BER (bit error rate) y número de operaciones sobre un sistema BICM (bit-interleaved coded modulation ) equivalente a DVB-T2 en escenarios TDT utilizando una detección LSD (list sphere decoder ). Para resolver el problema de la complejidad variable del algoritmo LSD, se realiza un rediseño del ya propuesto LFSD (list fixed-complexity sphere decoder ) para técnicas de multiplexación espacial considerando la estructura de los códigos FRFD SFBC. Asimismo, se evalúa el número de candidatos que ofrece un funcionamiento más eficiente con menor coste computacional. Los resultados de simulación basados en curvas de BER muestran rendimientos cercanos al detector LSD manteniendo el número de operaciones constante. Por lo tanto, este nuevo diseño permite su eficiente y práctica implementación en dispositivos reales.Doktoretza-tesi honen gai nagusia Lurreko Telebista Digitalerako antena anitzeko dibertsitate tekniken portaera ikertzea da, hartzailerako konplexutasun baxuko algoritmoen diseinua oinarri hartuta. Horretarako, Europako DVB-T eta DVB-T2 telebista digitaleko estandarren igorle-hartzaile kateen simulagailua inplementatzeaz gain, dibertsitate eta MIMO ( multipleinput multiple-output ) algoritmoak garatu eta aztertu dira. Lehenengo helburu gisa, CDD (cyclic delay diversity ), Alamouti kodean oinarritutako SFBC (space-frequency block coding ) eta MRC (maximum ratio combining ) teknikak ebaluatu dira Rayleigh eta Ricean ingurunetan, bai komunikazio nko zein mugikorretarako. Argitaratu berri den DVB-T2 estandarrak antena anitzeko prozesaketa telebista sistema digitalean sartu duenez, teknologia honen analisia egin da maiztasun bakarreko telebista sareetarako SFN (single frequency network ). Tesiaren helburu nagusia FRFD (full-rate full-diversity ) SFBC kodigoen ikerketa eta hauek telebista digitalaren estandar berrietan sartzea ahalbidetuko dituzten detekzio sistemen diseinua izan da. Kanalen kodi kazio indartsuagoak erabiltzeak, LDPC ( low-density parity check ) kodeak esaterako, MAP (maximum a posteriori ) algoritmoan oinarritutako soft irteeradun detektoreen erabilera dakar berekin, detekzioaren konplexutasuna areagotuz. Bi FRFD kode aukeratu dira errendimendu eta konplexutasun analisiak DVB-T2 bezalako BICM (bit-interleaved coded modulation ) sistemetan egiteko. Alde batetik, irabazi maximoa lortzen duen Golden kodea eta, bestetik, konplexutasun txikiagoa duen Sezginer eta Sarik proposatutako kodea erabili dira. Bit errore edo BER (bit error rate) tasan eta konputazio kostuan oinarrituta, emaitzak aurkeztu dira zerrenda dekodeatzaile esferikoa ( list sphere decoder, LSD) erabiliz. LSD-aren konplexutasun aldakorraren arazoa konpontzeko, ezpazio-multiplexazioko teknikarako LFSD (list xed-complexity sphere decoder ) algoritmoaren berdiseinua garatu da, FRFD SFBC kodeen egitura berezia kontuan hartuta. Algoritmoaren eraginkortasuna maximizatzeko kandidatuen zenbakia ebaluatzen da baita ere. LSD-en antzeko errendimendua duten BER gra ketan oinarritutako simulazio emaitzak aurkezten dira, eragiketa kopurua konstante eta LSD-arenaren baino murritzagoa mantenduz. Beraz, proposatutako diseinu eraginkorrak, FRFD SFBC antena anitzeko dibertsitatean oinarritutako eskemen inplementazioa ahalbidetu dezakete telebista digitalaren estandar berrietarako

High Throughput VLSI Architecture for Soft-Output MIMO Detection Based on A Greedy Graph Algorithm

Maximum-likelihood (ML) decoding is a very computational- intensive task for multiple-input multiple-output (MIMO) wireless channel detection. This paper presents a new graph based algorithm to achieve near ML performance for soft MIMO detection. Instead of using the traditional tree search based structure, we represent the search space of the MIMO signals with a directed graph and a greedy algorithm is ap- plied to compute the a posteriori probability (APP) for each transmitted bit. The proposed detector has two advantages: 1) it keeps a fixed throughput and has a regular and parallel datapath structure which makes it amenable to high speed VLSI implementation, and 2) it attempts to maximize the a posteriori probability by making the locally optimum choice at each stage with the hope of finding the global minimum Euclidean distance for every transmitted bit x_k element of {-1, +1}. Compared to the soft K-best detector, the proposed solution significantly reduces the complexity because sorting is not required, while still maintaining good bit error rate (BER) performance. The proposed greedy detection algorithm has been designed and synthesized for a 4 x 4 16-QAM MIMO system in a TSMC 65 nm CMOS technology. The detector achieves a maximum throughput of 600 Mbps with a 0.79 mm2 core area.Nokia CorporationNational Science Foundatio

Energy Efficient VLSI Circuits for MIMO-WLAN

Mobile communication - anytime, anywhere access to data and communication services - has been continuously increasing since the operation of the first wireless communication link by Guglielmo Marconi. The demand for higher data rates, despite the limited bandwidth, led to the development of multiple-input multiple-output (MIMO) communication which is often combined with orthogonal frequency division multiplexing (OFDM). Together, these two techniques achieve a high bandwidth efficiency. Unfortunately, techniques such as MIMO-OFDM significantly increase the signal processing complexity of transceivers. While fast improvements in the integrated circuit (IC) technology enabled to implement more signal processing complexity per chip, large efforts had and have to be done for novel algorithms as well as for efficient very large scaled integration (VLSI) architectures in order to meet today's and tomorrow's requirements for mobile wireless communication systems. In this thesis, we will present architectures and VLSI implementations of complete physical (PHY) layer application specific integrated circuits (ASICs) under the constraints imposed by an industrial wireless communication standard. Contrary to many other publications, we do not elaborate individual components of a MIMO-OFDM communication system stand-alone, but in the context of the complete PHY layer ASIC. We will investigate the performance of several MIMO detectors and the corresponding preprocessing circuits, being integrated into the entire PHY layer ASIC, in terms of achievable error-rate, power consumption, and area requirement. Finally, we will assemble the results from the proposed PHY layer implementations in order to enhance the energy efficiency of a transceiver. To this end, we propose a cross-layer optimization of PHY layer and medium access control (MAC) layer

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