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Author: Chen Shen
Publisher:
ISBN:
Category :
Languages : en
Pages : 63
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Book Description
Abstract: Multiple-input multiple-output (MIMO) technique in communication system has been widely researched. Compared with single-input single-output (SISO) communication, its properties of higher throughput, more ecient spectrum and usage make it one of the most significant technology in modern wireless communications. In MIMO system, sphere detection is the fundamental part. The purpose of traditional sphere detection is to achieve the maximum likelihood (ML) demodulation of the MIMO system. However, with the development of advanced forward error correction (FEC) techniques, such as the Convolutional code, Turbo code and LDPC code, the sphere detection algorithms that can provide soft information for the outer decoder attract more interests recently. Considering the computing complexity of generating the soft information, it is important to develop a high-speed VLSI architecture for MIMO detection. The first part of this thesis is about MIMO sphere detection algorithms. Two sphere detection algorithms are introduced. The depth first Schnorr-Euchner (SE) algorithm which generates the ML detection solution and the width first K-BEST algorithm which only generates the nearly-ML detection solution but more efficient in implementation are presented. Based on these algorithms, an improved nearly-ML algorithm with lower complexity and limited performance lose, compared with traditional K-BEST algorithms, is presented. The second part is focused on the hardware design. A 4*4 16-QAM MIMO detection system which can generate both soft information and hard decision solution is designed and implemented in FPGA. With the fully pipelined and parallel structure, it can achieve a throughput of 3.7 Gbps. In this part, the improved nearly-ML algorithm is implmented as a detector to generat both the hard output and candidate list. Then, a soft information calculation block is designed to succeed the detector and produce the log-likelihood ratio (LLR) values for every bit as the soft output.
Author: Chen Shen
Publisher:
ISBN:
Category :
Languages : en
Pages : 63
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Book Description
Abstract: Multiple-input multiple-output (MIMO) technique in communication system has been widely researched. Compared with single-input single-output (SISO) communication, its properties of higher throughput, more ecient spectrum and usage make it one of the most significant technology in modern wireless communications. In MIMO system, sphere detection is the fundamental part. The purpose of traditional sphere detection is to achieve the maximum likelihood (ML) demodulation of the MIMO system. However, with the development of advanced forward error correction (FEC) techniques, such as the Convolutional code, Turbo code and LDPC code, the sphere detection algorithms that can provide soft information for the outer decoder attract more interests recently. Considering the computing complexity of generating the soft information, it is important to develop a high-speed VLSI architecture for MIMO detection. The first part of this thesis is about MIMO sphere detection algorithms. Two sphere detection algorithms are introduced. The depth first Schnorr-Euchner (SE) algorithm which generates the ML detection solution and the width first K-BEST algorithm which only generates the nearly-ML detection solution but more efficient in implementation are presented. Based on these algorithms, an improved nearly-ML algorithm with lower complexity and limited performance lose, compared with traditional K-BEST algorithms, is presented. The second part is focused on the hardware design. A 4*4 16-QAM MIMO detection system which can generate both soft information and hard decision solution is designed and implemented in FPGA. With the fully pipelined and parallel structure, it can achieve a throughput of 3.7 Gbps. In this part, the improved nearly-ML algorithm is implmented as a detector to generat both the hard output and candidate list. Then, a soft information calculation block is designed to succeed the detector and produce the log-likelihood ratio (LLR) values for every bit as the soft output.
Author: Milos Jorgovanovic
Publisher:
ISBN:
Category :
Languages : en
Pages : 124
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Author: 黃淳賢
Publisher:
ISBN:
Category :
Languages : en
Pages : 68
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Author: Ibrahim A. Bello
Publisher: Springer Nature
ISBN: 3031045122
Category : Technology & Engineering
Languages : en
Pages : 162
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Book Description
This book provides a detailed overview of detection algorithms for multiple-input multiple-output (MIMO) communications systems focusing on their hardware realisation. The book begins by analysing the maximum likelihood detector, which provides the optimal bit error rate performance in an uncoded communications system. However, the maximum likelihood detector experiences a high complexity that scales exponentially with the number of antennas, which makes it impractical for real-time communications systems. The authors proceed to discuss lower-complexity detection algorithms such as zero-forcing, sphere decoding, and the K-best algorithm, with the aid of detailed algorithmic analysis and several MATLAB code examples. Furthermore, different design examples of MIMO detection algorithms and their hardware implementation results are presented and discussed. Finally, an ASIC design flow for implementing MIMO detection algorithms in hardware is provided, including the system simulation and modelling steps and register transfer level modelling using hardware description languages. Provides an overview of MIMO detection algorithms and discusses their corresponding hardware implementations in detail; Highlights architectural considerations of MIMO detectors in achieving low power consumption and high throughput; Discusses design tradeoffs that will guide readers’ efforts when implementing MIMO algorithms in hardware; Describes a broad range of implementations of different MIMO detectors, enabling readers to make informed design decisions based on their application requirements.
Author: Richeek Arya
Publisher:
ISBN:
Category :
Languages : en
Pages :
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In this thesis we have presented an implementation of soft Multi Input Multi Output (MIMO) detection, single tree search algorithm on Graphics Processing Units (GPUs). We have compared its performance on different GPUs and a Central Processing Unit (CPU). We have also done a performance study of iterative decoding algorithms. We have shown that by increasing the number of outer iterations error rate performance can be further improved. GPUs are specialized devices specially designed to accelerate graphics processing. They are massively parallel devices which can run thousands of threads simultaneously. Because of their tremendous processing power there is an increasing interest in using them for scientific and general purpose computations. Hence companies like Nvidia, Advanced Micro Devices (AMD) etc. have started their support for General Purpose GPU (GPGPU) applications. Nvidia came up with Compute Unified Device Architecture (CUDA) to program its GPUs. Efforts are made to come up with a standard language for parallel computing that can be used across platforms. OpenCL is the first such language which is supported by all major GPU and CPU vendors. MIMO detector has a high computational complexity. We have implemented a soft MIMO detector on GPUs and studied its throughput and latency performance. We have shown that a GPU can give throughput of up to 4Mbps for a soft detection algorithm which is more than sufficient for most general purpose tasks like voice communication etc. Compare to CPU a throughput increase of ~7x is achieved. We also compared the performances of two GPUs one with low computational power and one with high computational power. These comparisons show effect of thread serialization on algorithms with the lower end GPU's execution time curve shows a slope of 1/2. To further improve error rate performance iterative decoding techniques are employed where a feedback path is employed between detector and decoder. With an eye towards GPU implementation we have explored these algorithms. Better error rate performance however, comes at a price of higher power dissipation and more latency. By simulations we have shown that one can predict based on the Signal to Noise Ratio (SNR) values how many iterations need to be done before getting an acceptable Bit Error Rate (BER) and Frame Error Rate (FER) performance. Iterative decoding technique shows that a SNR gain of ~1:5dB is achieved when number of outer iterations is increased from zero. To reduce the complexity one can adjust number of possible candidates the algorithm can generate. We showed that where a candidate list of 128 is not sufficient for acceptable error rate performance for a 4x4 MIMO system using 16-QAM modulation scheme, performances are comparable with the list size of 512 and 1024 respectively.
Author: Albert Sabban
Publisher: BoD – Books on Demand
ISBN: 1839683457
Category : Technology & Engineering
Languages : en
Pages : 282
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Book Description
The main objective of this book is to present novel radio frequency (RF) antennas for 5G, IOT, and medical applications. The book is divided into four sections that present the main topics of radio frequency antennas. The rapid growth in development of cellular wireless communication systems over the last twenty years has resulted in most of world population owning smartphones, smart watches, I-pads, and other RF communication devices. Efficient compact wideband antennas are crucial in RF communication devices. This book presents information on planar antennas, cavity antennas, Vivaldi antennas, phased arrays, MIMO antennas, beamforming phased array reconfigurable Pabry-Perot cavity antennas, and time modulated linear array.
Author:
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ISBN:
Category :
Languages : en
Pages :
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This work focuses on the design and implementation aspects of Multi-Input Multi-Output (MIMO) decoders for multi-antenna communications. These decoders are used to determine, either optimally or sub-optimally, the bits encoded and transmitted over a wireless channel with more than one antenna. Present standards, such as 802.11n and 4G, call for systems with more than the present two antennas. Additionally, the need for future considerations of mobility along with lowered current limits of smaller technology nodes, calls for greater power awareness in the design of MIMO decoders. The presence of multiple antennas brings with them a) an exponentially large space for a min-cost search for the solution and b) non-trivial VLSI requirements to deal with additional dimensions of the wireless channel. Additionally, the conditions under which a MIMO decoder is used would change in terms of the Signal to Noise Ratio (SNR) values. This requires considerations in the multiple axes for a decoder implementation: Power, Delay, throughput and algorithmic performance. Of the many options available, Sphere Decoding (SD) has become a popular implementation of MIMO detection due to its improved performance at lower hardware complexity in comparison with Maximum Likelihood methods for optimal algorithmic performance. ASIC implementations have proven the feasibility of this method but fail to effectively address the issue of energy efficiency (b/s/mW). In this work, we investigate the architectural and design space of multi-antenna decoders. We show that systems that allow for tradeoffs along multiple axes are more likely to achieve energy optimality due to a changing usage environment. Multi-antenna systems are unique because they can exploit parallelism which could aid in amortizing the constraints on design. We design and implement improved architectures that exploit a combination of a deeper pipelines and simple single-port read and write memories to increase the energy efficiency (b.
Author:
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Languages : en
Pages :
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Author: Tzi-Dar Chiueh
Publisher: John Wiley & Sons
ISBN: 1118188217
Category : Technology & Engineering
Languages : en
Pages : 388
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Book Description
The Second Edition of OFDM Baseband Receiver Design for Wirless Communications, this book expands on the earlier edition with enhanced coverage of MIMO techniques, additional baseband algorithms, and more IC design examples. The authors cover the full range of OFDM technology, from theories and algorithms to architectures and circuits. The book gives a concise yet comprehensive look at digital communication fundamentals before explaining signal processing algorithms in receivers. The authors give detailed treatment of hardware issues - from architecture to IC implementation. Links OFDM and MIMO theory with hardware implementation Enables the reader to transfer communication received concepts into hardware; design wireless receivers with acceptable implemntation loss; achieve low-power designs Covers the latest standards, such as DVB-T2, WiMax, LTE and LTE-A Includes more baseband algorithms, like soft-decoding algorithms such as BCJR and SOVA Expanded treatment of channel models, detection algorithms and MIMO techniques Features concrete design examples of WiMAX systems and cognitive radio apllications Companion website with lecture slides for instructors Based on materials developed for a course in digital communication IC design, this book is ideal for graduate students and researchers in VLSI design, wireless communications, and communications signal processing. Practicing engineers working on algorithms or hardware for wireless communications devices will also find this to be a key reference.
Author: Jun Zheng
Publisher:
ISBN:
Category :
Languages : en
Pages : 228
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Book Description
Using multiple antennas at both the transmitter and the receiver is one of the most promising techniques that can offer significant increases in channel capacity of a communication system in a wireless fading environment. However, the performance of the MIMO system depends heavily upon the availability of the channel state information (CSI) at the transmitter (CSIT) and at the receiver (CSIR). In this dissertation, we focus our attention on the design and analysis of MIMO systems over wireless fading channels with practical CSI assumptions, which can broadly be divided into the following two categories. The first part considers the development of a general framework for the analysis of multiple antenna systems with finite-rate feedback, wherein the CSI is quantized at the receiver and conveyed back to the transmitter through a rate-constrained reverse link. Inspired by the results of classical high resolution quantization theory, the problem of finite rate quantized communication system is formulated as a general fixed-rate vector quantization problem with side information available at the encoder (or the quantizer) but unavailable at the decoder. The framework of the quantization problem is sufficiently general to include quantization schemes with general non-mean square distortion functions, and constrained source vectors. Asymptotic distortion analysis of the proposed general quantization problem is provided by extending the vector version of the Bennett's integral. Specifically, tight lower and upper bounds of the average asymptotic distortion are provided together with useful insights from a source coding perspective. The proposed general methodology provides a powerful analytical tool to study a wide range of finite-rate feedback systems which includes both MISO systems over spatially correlated fading channels and MIMO systems over i.i.d. fading channels. The established framework is also versatile enough to provide analysis of sub-optimal mismatched CSI quantizers and quantizers with transformed codebooks. The second part of this dissertation is focused the on the design and analysis of MIMO systems over fading channels with CSI unavailable both at the transmitter and at the receiver. To be specific, we first provide an improved capacity lower bound for MIMO systems with unknown CSI. By analyzing (and optimizing) the proposed capacity lower bound with respect to different system parameters, we improve our intuition and understanding of the effects of training on the overall performance of MIMO systems under unknown CSI assumptions. Moreover, based on the capacity analysis results, we also provide the design of practical LDPC-coded MIMO systems under the same unknown CSI assumption at both component level and structural level. We first propose at the component level several soft-input soft-output MIMO detectors whose performances are much better than the conventional MMSE-based detectors. At the structural level, an unconventional iterative decoding scheme is proposed whose structure leads to a simple and efficient LDPC code degree profile optimization algorithm with proven global optimality and guaranteed convergence from any initialization.
