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Author: Xiaoguang Dai Publisher: Open Dissertation Press ISBN: 9781361255070 Category : Languages : en Pages :
Book Description
This dissertation, "Receiver Complexity Reduction of Multiple-input Multiple-output Wireless Communication Systems" by Xiaoguang, Dai, 戴晓光, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. DOI: 10.5353/th_b4658950 Subjects: Space time codes MIMO systems Wireless communication systems
Author: Xiaoguang Dai Publisher: Open Dissertation Press ISBN: 9781361255070 Category : Languages : en Pages :
Book Description
This dissertation, "Receiver Complexity Reduction of Multiple-input Multiple-output Wireless Communication Systems" by Xiaoguang, Dai, 戴晓光, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. DOI: 10.5353/th_b4658950 Subjects: Space time codes MIMO systems Wireless communication systems
Author: Lin Bai Publisher: Springer Science & Business Media ISBN: 3319049844 Category : Technology & Engineering Languages : en Pages : 313
Book Description
Multiple-input multiple-output (MIMO) systems can increase the spectral efficiency in wireless communications. However, the interference becomes the major drawback that leads to high computational complexity at both transmitter and receiver. In particular, the complexity of MIMO receivers can be prohibitively high. As an efficient mathematical tool to devise low complexity approaches that mitigate the interference in MIMO systems, lattice reduction (LR) has been widely studied and employed over the last decade. The co-authors of this book are world's leading experts on MIMO receivers, and here they share the key findings of their research over years. They detail a range of key techniques for receiver design as multiple transmitted and received signals are available. The authors first introduce the principle of signal detection and the LR in mathematical aspects. They then move on to discuss the use of LR in low complexity MIMO receiver design with respect to different aspects, including uncoded MIMO detection, MIMO iterative receivers, receivers in multiuser scenarios, and multicell MIMO systems.
Author: Publisher: ISBN: Category : Algorithms Languages : en Pages :
Book Description
Wireless communication devices are currently enjoying increasing popularity and widespread use. The constantly growing number of users, however, results in the shortage of the available spectrum. Various techniques have been proposed to increase the spectrum efficiency of wireless systems to solve the problem. Multiple Input Multiple Output (MIMO) is one solution that employs multiple antennas at the transmitter and receiver. The MIMO algorithms are usually highly complex and computationally intensive. This results in increased power consumption and reduced battery lifespan. This thesis investigates the complexity - performance trade-off of two MIMO algorithms. Space Time Block Coding (STBC) is a MIMO-based algorithm, which efficiently exploits spatial and temporal diversity. Recently, it has been specified in a number of 3G standards. However, not much attention has been paid to the implementation issues of this algorithm. One such issue, clipping of the Analog to Digital Converter (ADC) at the receiver, is described in the first part of the thesis (chapter 3). A small amount of clipping in an ADC can improve dynamic range and reduce the power consumption. However, the increased clipping distortion of the signal, can adversely affect the overall performance of the system. It will be shown in this dissertation that STBC are more sensitive to clipping, compared to the uncoded single antenna systems. Two receiver structures are considered: Direct Conversion (DC) structure, where the ADCs impose a square clipping function, and a Log-Polar structure, where ADC induces a circular clipping function. Log-Polar receivers were found to be clipping insensitive for the given target Symbol Error Rate (SER) of 1*10-3. This makes Log-Polar receivers an obvious choice for the system designers. The second part of the thesis (chapter 4) addresses the complexity problem associated with the QR decomposition algorithm, which is frequently used as a faster alternative to channel inversion in a MIMO scheme. Channel tracking can be employed with QR equalization in order to reduce the pilot overhead of a MIMO system in a non-stationary environment. QR decomposition is part of the QR equalization method and has to be performed in every instance that the channel estimate is obtained. The high rate of the QR decomposition, a computationally intensive technique, results in a high computational complexity per symbol. Some novel modifications are proposed to address this problem. Reducing the repetition rate of QR decompositions and tracking R (the upper triangular matrix) directly, while holding unitary matrix Q fixed, can significantly reduce complexity per symbol at the expense of some introduced error. Additional modification of the CORDIC algorithm (a square root- and division-free algorithm used to perform QR decomposition) results in more than 80% of computational complexity savings. Further, Minimum Mean Squared Error (MMSE) detection is applied to Least Mean Squared (LMS) based R tracking and channel tracking algorithms and then compared in complexity and performance to the Recursive Least Squares Decision Feedback Equalizer (RLS-DFE) tracking system in [1]. The R tracking scheme is shown to achieve more accurate channel estimates compared to the channel tracking scenario, but this advantage does not translate into better Bit Error Rate (BER) results due to errors on the first layer of the detector. Both LMS strategies have an inferior BER performance compared to the DFE RLS-based system of [1], and surprisingly the LMS schemes show no significant complexity improvement.
Author: Fan Jiang Publisher: ISBN: Category : Languages : en Pages :
Book Description
The tradeoff between the computational complexity and system performance in multipleinput multiple-output (MIMO) wireless communication systems is critical to practical applications. In this dissertation, we investigate efficient low-complexity data detection schemes from conventional small-scale to recent large-scale MIMO systems, with the targeted applications in terrestrial wireless communication systems, vehicular networks, and underwater acoustic communication systems. In the small-scale MIMO scenario, we study turbo equalization schemes for multipleinput multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) and multipleinput multiple-output single-carrier frequency division multiple access (MIMO SC-FDMA) systems. For the MIMO-OFDM system, we propose a soft-input soft-output sorted QR decomposition (SQRD) based turbo equalization scheme under imperfect channel estimation. We demonstrate the performance enhancement of the proposed scheme over the conventional minimum mean-square error (MMSE) based turbo equalization scheme in terms of system bit error rate (BER) and convergence performance. Furthermore, by jointly considering channel estimation error and the a priori information from the channel decoder, we develop low-complexity turbo equalization schemes conditioned on channel estimate for MIMO systems. Our proposed methods generalize the expressions used for MMSE and MMSE-SQRD based turbo equalizers, where the existing methods can be viewed as special cases. In addition, we extend the SQRD-based soft interference cancelation scheme to MIMO SC-FDMA systems where a multi-user MIMO scenario is considered. We show an improved system BER performance of the proposed turbo detection scheme over the conventional MMSE-based detection scheme. In the large-scale MIMO scenario, we focus on low-complexity detection schemes because computational complexity becomes critical issue for massive MIMO applications. We first propose an innovative approach of using the stair matrix in the development of massive MIMO detection schemes. We demonstrate the applicability of the stair matrix through the study of the convergence conditions. We then investigate the system performance and demonstrate that the convergence rate and the system BER are much improved over the diagonal matrix based approach with the same system configuration. We further investigate low-complexity and fast processing detection schemes for massive MIMO systems where a block diagonal matrix is utilized in the development. Using a parallel processing structure, the processing time can be much reduced. We investigate the convergence performance through both the probability that the convergence conditions are satisfied and the convergence rate, and evaluate the system performance in terms of computational complexity, system BER, and the overall processing time. Using our proposed approach, we extend the block Gauss-Seidel method to large-scale array signal detection in underwater acoustic (UWA) communications. By utilizing a recently proposed computational efficient statistic UWA channel model, we show that the proposed scheme can effectively approach the system performance of the original Gauss-Seidel method, but with much reduced processing delay.
Author: Hien Quoc Ngo Publisher: Linköping University Electronic Press ISBN: 9175191474 Category : Languages : en Pages : 69
Book Description
The last ten years have seen a massive growth in the number of connected wireless devices. Billions of devices are connected and managed by wireless networks. At the same time, each device needs a high throughput to support applications such as voice, real-time video, movies, and games. Demands for wireless throughput and the number of wireless devices will always increase. In addition, there is a growing concern about energy consumption of wireless communication systems. Thus, future wireless systems have to satisfy three main requirements: i) having a high throughput; ii) simultaneously serving many users; and iii) having less energy consumption. Massive multiple-input multiple-output (MIMO) technology, where a base station (BS) equipped with very large number of antennas (collocated or distributed) serves many users in the same time-frequency resource, can meet the above requirements, and hence, it is a promising candidate technology for next generations of wireless systems. With massive antenna arrays at the BS, for most propagation environments, the channels become favorable, i.e., the channel vectors between the users and the BS are (nearly) pairwisely orthogonal, and hence, linear processing is nearly optimal. A huge throughput and energy efficiency can be achieved due to the multiplexing gain and the array gain. In particular, with a simple power control scheme, Massive MIMO can offer uniformly good service for all users. In this dissertation, we focus on the performance of Massive MIMO. The dissertation consists of two main parts: fundamentals and system designs of Massive MIMO. In the first part, we focus on fundamental limits of the system performance under practical constraints such as low complexity processing, limited length of each coherence interval, intercell interference, and finite-dimensional channels. We first study the potential for power savings of the Massive MIMO uplink with maximum-ratio combining (MRC), zero-forcing, and minimum mean-square error receivers, under perfect and imperfect channels. The energy and spectral efficiency tradeoff is investigated. Secondly, we consider a physical channel model where the angular domain is divided into a finite number of distinct directions. A lower bound on the capacity is derived, and the effect of pilot contamination in this finite-dimensional channel model is analyzed. Finally, some aspects of favorable propagation in Massive MIMO under Rayleigh fading and line-of-sight (LoS) channels are investigated. We show that both Rayleigh fading and LoS environments offer favorable propagation. In the second part, based on the fundamental analysis in the first part, we propose some system designs for Massive MIMO. The acquisition of channel state information (CSI) is very importantin Massive MIMO. Typically, the channels are estimated at the BS through uplink training. Owing to the limited length of the coherence interval, the system performance is limited by pilot contamination. To reduce the pilot contamination effect, we propose an eigenvalue-decomposition-based scheme to estimate the channel directly from the received data. The proposed scheme results in better performance compared with the conventional training schemes due to the reduced pilot contamination. Another important issue of CSI acquisition in Massive MIMO is how to acquire CSI at the users. To address this issue, we propose two channel estimation schemes at the users: i) a downlink "beamforming training" scheme, and ii) a method for blind estimation of the effective downlink channel gains. In both schemes, the channel estimation overhead is independent of the number of BS antennas. We also derive the optimal pilot and data powers as well as the training duration allocation to maximize the sum spectral efficiency of the Massive MIMO uplink with MRC receivers, for a given total energy budget spent in a coherence interval. Finally, applications of Massive MIMO in relay channels are proposed and analyzed. Specifically, we consider multipair relaying systems where many sources simultaneously communicate with many destinations in the same time-frequency resource with the help of a massive MIMO relay. A massive MIMO relay is equipped with many collocated or distributed antennas. We consider different duplexing modes (full-duplex and half-duplex) and different relaying protocols (amplify-and-forward, decode-and-forward, two-way relaying, and one-way relaying) at the relay. The potential benefits of massive MIMO technology in these relaying systems are explored in terms of spectral efficiency and power efficiency.
Author: Publisher: ISBN: Category : Languages : en Pages : 30
Book Description
Multiple-input multiple-output (MI MO) wireless communication provides a number of advantages over traditional single-input single-output (SISO) approaches including increased data rates for a given total transmit power and improved robustness to interference. Many of these advantages depend strongly upon the details of the receiver implementation. For practical communication systems a competition between communication performance and computational complexity exists. To reduce computation complexity suboptimal receivers are commonly employed. In this paper the details of a variety of receivers are incorporated into the effects of the channel so that information-theoretic performance bounds can be exploited to evaluate receiver approaches. The performance of these receivers is investigated for a range of environments. Two classes of environments are considered: first channel complexity characterized by the shape of the narrowband channel-matrix singular-value distribution and second external interference Receiver approaches include minimum-mean-squared error minimum interference and multichannel multiuser detection (MCMUD) given various assumed limitations on channel and interference estimation Receiver performance implications are also demonstrated using experimental data.
Author: Xiaoguang Dai
Author: Xiaoguang Dai
Author: Xiaoguang Dai
Author: Lin Bai
Author: 
Author: Fan Jiang
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Author: Hien Quoc Ngo
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