29 research outputs found

    Parallel QRD-M encoder for multi-user MIMO systems

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    International audienceIn the context of multi-user precoding, the idea behind vector perturbation (VP) lies in adding an integer vector to the data vector such that the overall transmit power is reduced, where the performance at the users end is consequently improved. In the literature, several techniques have been proposed to nd a quasi-optimum perturbing vector, where this process was represented as an integer lattice search problem. In this paper, we propose a parallel QRD-M encoder (PQRDME) that, besides attaining a quasi-optimum diversity order, leads to tremendous reduction in the latency of the vector perturbation stage. Based on the set grouping, the proposed encoder transforms the full tree-search of the conventional QRDME into partial trees that can be pipelined to increase the encoding throughput. We evaluate the proposed algorithm under several scenarios with both perfect channel state information (PCSI) and imperfect CSI (ICSI) at the transmitter side, where simulation results show robust performance when compared to the optimum encoder

    Novel LDPC coding and decoding strategies: design, analysis, and algorithms

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    In this digital era, modern communication systems play an essential part in nearly every aspect of life, with examples ranging from mobile networks and satellite communications to Internet and data transfer. Unfortunately, all communication systems in a practical setting are noisy, which indicates that we can either improve the physical characteristics of the channel or find a possible systematical solution, i.e. error control coding. The history of error control coding dates back to 1948 when Claude Shannon published his celebrated work “A Mathematical Theory of Communication”, which built a framework for channel coding, source coding and information theory. For the first time, we saw evidence for the existence of channel codes, which enable reliable communication as long as the information rate of the code does not surpass the so-called channel capacity. Nevertheless, in the following 60 years none of the codes have been proven closely to approach the theoretical bound until the arrival of turbo codes and the renaissance of LDPC codes. As a strong contender of turbo codes, the advantages of LDPC codes include parallel implementation of decoding algorithms and, more crucially, graphical construction of codes. However, there are also some drawbacks to LDPC codes, e.g. significant performance degradation due to the presence of short cycles or very high decoding latency. In this thesis, we will focus on the practical realisation of finite-length LDPC codes and devise algorithms to tackle those issues. Firstly, rate-compatible (RC) LDPC codes with short/moderate block lengths are investigated on the basis of optimising the graphical structure of the tanner graph (TG), in order to achieve a variety of code rates (0.1 < R < 0.9) by only using a single encoder-decoder pair. As is widely recognised in the literature, the presence of short cycles considerably reduces the overall performance of LDPC codes which significantly limits their application in communication systems. To reduce the impact of short cycles effectively for different code rates, algorithms for counting short cycles and a graph-related metric called Extrinsic Message Degree (EMD) are applied with the development of the proposed puncturing and extension techniques. A complete set of simulations are carried out to demonstrate that the proposed RC designs can largely minimise the performance loss caused by puncturing or extension. Secondly, at the decoding end, we study novel decoding strategies which compensate for the negative effect of short cycles by reweighting part of the extrinsic messages exchanged between the nodes of a TG. The proposed reweighted belief propagation (BP) algorithms aim to implement efficient decoding, i.e. accurate signal reconstruction and low decoding latency, for LDPC codes via various design methods. A variable factor appearance probability belief propagation (VFAP-BP) algorithm is proposed along with an improved version called a locally-optimized reweighted (LOW)-BP algorithm, both of which can be employed to enhance decoding performance significantly for regular and irregular LDPC codes. More importantly, the optimisation of reweighting parameters only takes place in an offline stage so that no additional computational complexity is required during the real-time decoding process. Lastly, two iterative detection and decoding (IDD) receivers are presented for multiple-input multiple-output (MIMO) systems operating in a spatial multiplexing configuration. QR decomposition (QRD)-type IDD receivers utilise the proposed multiple-feedback (MF)-QRD or variable-M (VM)-QRD detection algorithm with a standard BP decoding algorithm, while knowledge-aided (KA)-type receivers are equipped with a simple soft parallel interference cancellation (PIC) detector and the proposed reweighted BP decoders. In the uncoded scenario, the proposed MF-QRD and VM-QRD algorithms are shown to approach optimal performance, yet require a reduced computational complexity. In the LDPC-coded scenario, simulation results have illustrated that the proposed QRD-type IDD receivers can offer near-optimal performance after a small number of detection/decoding iterations and the proposed KA-type IDD receivers significantly outperform receivers using alternative decoding algorithms, while requiring similar decoding complexity

    Hardware implementation of multiple-input multiple-output transceiver for wireless communication

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    This dissertation proposes an efficient hardware implementation scheme for iterative multi-input multi-output orthogonal frequency-division multiplexing (MIMO-OFDM) transceiver. The transmitter incorporates linear precoder designed with instantaneous channel state information (CSI). The receiver implements MMSE-IC (minimum mean square error interference cancelation) detector, channel estimator, low-density parity-check (LDPC) decoder and other supporting modules. The proposed implementation uses QR decomposition (QRD) of complex-valued matrices with four co-ordinate rotation digital computer (CORDIC) cores and back substitution to achieve the best tradeoff between resource and throughput. The MIMO system is used in field test and the results indicate that the instantaneous CSI varies very fast in practices and the performance of linear precoder designed with instantaneous CSI is limited. Instead, statistic CSI had to be used. This dissertation also proposes a higher-rank principle Kronecker model (PKM). That exploits the statistic CSI to simulate the fading channels. The PKM is constructed by decomposing the channel correlation matrices with the higher-order singular value decomposition (HOSVD) method. The proposed PKM-HOSVD model is validated by extensive field experiments conducted for 4-by-4 MIMO systems in both indoor and outdoor environments. The results confirm that the statistic CSI varies slowly and the PKM-HOSVD will be helpful in the design of linear precoders. --Abstract, page iv

    Application of integer quadratic programming in detection of high-dimensional wireless systems

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    High-dimensional wireless systems have recently generated a great deal of interest due to their ability to accommodate increasing demands for high transmission data rates with high communication reliability. Examples of such large-scale systems include single-input, single-output symbol spread OFDM system, large-scale single-user multi-input multi-output (MIMO) OFDM systems, and large-scale multiuser MIMO systems. In these systems, the number of symbols required to be jointly detected at the receiver is relatively large. The challenge with the practical realization of these systems is to design a detection scheme that provides high communication reliability with reasonable computational complexity, even as the number of simultaneously transmitted independent communication signals becomes very large.^ Most of the optimal or near-optimal detection techniques that have been proposed in the literature of relatively low-dimensional wireless systems, such as MIMO systems in which number of antennas is less than 10, become problematic for high-dimensional detection problems. That is, their performance degrades or the computational complexity becomes prohibitive, especially when higher-order QAM constellations are employed.^ In the first part of this thesis, we propose a near-optimal detection technique which offers a flexible trade-off between complexity and performance. The proposed technique formulates the detection problem in terms of Integer Quadratic Programming (IQP), which is then solved through a controlled Branch and Bound (BB) search tree algorithm. In addition to providing good performance, an important feature of this approach is that its computational complexity remains roughly the same even as we increase the constellation order from 4-QAM to 256-QAM. The performance of the proposed algorithm is investigated for both symbol spread OFDM systems and large-scale MIMO systems with both frequency selective and at fading channels.^ The second part of this work focuses on a reduced complexity version of IQP referred to as relaxed quadratic programming (QP). In particular, QP is used to reformulate two widely used detection schemes for MIMO OFDM: (1) Successive Interference Cancellation (SIC) and (2) Iterative Detecting and Decoding (IDD). First, SIC-based algorithms are derived via a QP formulation in contrast to using a linear MMSE detector at each stage. The resulting QP-SIC algorithms offer lower computational complexity than the SIC schemes that employ linear MMSE at each stage, especially when the dimension of the received signal vector is high. Three versions of QP-SIC are proposed based on various trade-offs between complexity and receiver performance; each of the three QP-SIC algorithms outperforms existing SIC techniques. Second, IDD-based algorithms are developed using a QP detector. We show how the soft information, in terms of the Log Likelihood Ratio (LLR), can be extracted from the QP detector. Further, the procedure for incorporating the a-priori information that is passed from the channel decoder to the QP detector is developed. Simulation results are presented demonstrating that the use of QP in IDD offers improved performance at the cost of a reasonable increase in complexity compared to linear detectors

    COMPLEXITY REDUCED CHANNEL ESTIMATION IN WIMAX ENVIRONMENT FOR MIMO–OFDM SYSTEM

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    Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) are considered to be major methods for the ensuing high performance in next generation mobile communications. The undesirable effects on the transmitted signals need to be addressed and eliminated to improve the capacity of the systems. These effects depend on the physical properties of the channel. Hence, there is a need to provide perfect estimate of the channel to counteract these effects and thereby delivering precise base-band processes at the receiving end of the system such as signal demodulation and decoding. In this paper, the channel between multiple antenna elements are investigated and analysed for optimum technique with less complexity and less power requirement to estimate the characteristics of the channel. The bit error rate (BER) and normalised mean square error (NMSE) of the channels in MIMO-OFDM systems are examined for different channel tracking techniques. The simulation results are measured to investigate the working of the system model with different algorithms over Worldwide Interoperability for Microwave Access channel. An efficient QRD method is suggested in this paper based on the available system resources and specifications

    Multiple Access Techniques for Next Generation Wireless: Recent Advances and Future Perspectives

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    The advances in multiple access techniques has been one of the key drivers in moving from one cellular generation to another. Starting from the first generation, several multiple access techniques have been explored in different generations and various emerging multiplexing/multiple access techniques are being investigated for the next generation of cellular networks. In this context, this paper first provides a detailed review on the existing Space Division Multiple Access (SDMA) related works. Subsequently, it highlights the main features and the drawbacks of various existing and emerging multiplexing/multiple access techniques. Finally, we propose a novel concept of clustered orthogonal signature division multiple access for the next generation of cellular networks. The proposed concept envisions to employ joint antenna coding in order to enhance the orthogonality of SDMA beams with the objective of enhancing the spectral efficiency of future cellular networks

    Adaptive Baseband Pro cessing and Configurable Hardware for Wireless Communication

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    The world of information is literally at one’s fingertips, allowing access to previously unimaginable amounts of data, thanks to advances in wireless communication. The growing demand for high speed data has necessitated theuse of wider bandwidths, and wireless technologies such as Multiple-InputMultiple-Output (MIMO) have been adopted to increase spectral efficiency.These advanced communication technologies require sophisticated signal processing, often leading to higher power consumption and reduced battery life.Therefore, increasing energy efficiency of baseband hardware for MIMO signal processing has become extremely vital. High Quality of Service (QoS)requirements invariably lead to a larger number of computations and a higherpower dissipation. However, recognizing the dynamic nature of the wirelesscommunication medium in which only some channel scenarios require complexsignal processing, and that not all situations call for high data rates, allowsthe use of an adaptive channel aware signal processing strategy to provide adesired QoS. Information such as interference conditions, coherence bandwidthand Signal to Noise Ratio (SNR) can be used to reduce algorithmic computations in favorable channels. Hardware circuits which run these algorithmsneed flexibility and easy reconfigurability to switch between multiple designsfor different parameters. These parameters can be used to tune the operations of different components in a receiver based on feedback from the digitalbaseband. This dissertation focuses on the optimization of digital basebandcircuitry of receivers which use feedback to trade power and performance. Aco-optimization approach, where designs are optimized starting from the algorithmic stage through the hardware architectural stage to the final circuitimplementation is adopted to realize energy efficient digital baseband hardwarefor mobile 4G devices. These concepts are also extended to the next generation5G systems where the energy efficiency of the base station is improved.This work includes six papers that examine digital circuits in MIMO wireless receivers. Several key blocks in these receiver include analog circuits thathave residual non-linearities, leading to signal intermodulation and distortion.Paper-I introduces a digital technique to detect such non-linearities and calibrate analog circuits to improve signal quality. The concept of a digital nonlinearity tuning system developed in Paper-I is implemented and demonstratedin hardware. The performance of this implementation is tested with an analogchannel select filter, and results are presented in Paper-II. MIMO systems suchas the ones used in 4G, may employ QR Decomposition (QRD) processors tosimplify the implementation of tree search based signal detectors. However,the small form factor of the mobile device increases spatial correlation, whichis detrimental to signal multiplexing. Consequently, a QRD processor capableof handling high spatial correlation is presented in Paper-III. The algorithm and hardware implementation are optimized for carrier aggregation, which increases requirements on signal processing throughput, leading to higher powerdissipation. Paper-IV presents a method to perform channel-aware processingwith a simple interpolation strategy to adaptively reduce QRD computationcount. Channel properties such as coherence bandwidth and SNR are used toreduce multiplications by 40% to 80%. These concepts are extended to usetime domain correlation properties, and a full QRD processor for 4G systemsfabricated in 28 nm FD-SOI technology is presented in Paper-V. The designis implemented with a configurable architecture and measurements show thatcircuit tuning results in a highly energy efficient processor, requiring 0.2 nJ to1.3 nJ for each QRD. Finally, these adaptive channel-aware signal processingconcepts are examined in the scope of the next generation of communicationsystems. Massive MIMO systems increase spectral efficiency by using a largenumber of antennas at the base station. Consequently, the signal processingat the base station has a high computational count. Paper-VI presents a configurable detection scheme which reduces this complexity by using techniquessuch as selective user detection and interpolation based signal processing. Hardware is optimized for resource sharing, resulting in a highly reconfigurable andenergy efficient uplink signal detector
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