Extending a Fixed-Complexity Sphere Decoder to Obtain Likelihood Information for Turbo-MIMO Systems

The Journal of Korean Institute of Communications and Informati

Choi

2014

With the increasing demands on high data rate, there has been growing interests in multi-input multi-output (MIMO) technology based on spatial multiplexing (SM) since it can transmit independent information in each spatial stream. Recent standards such as 3GPP LTE-advanced and IEEE 802.11ac support up to eight spatial streams, and massive MIMO and mm-wave systems that are expected to be included in beyond 4G systems are considering employment of tens to hundreds of antennas. Since the complexity of the optimum maximum likelihood based detection method increases exponentially with the number of antennas, low-complexity SM MIMO detection becomes more critical as the number of antenna increases. In this paper, we first review the results on the detection schemes for SM MIMO systems. In addition, massive MIMO reception schemes based on simple linear filtering which does not require exponential increment of complexity will be explained, followed by brief description on receiver design for future high dimensional SM MIMO systems.

Section: ⅰ 서 론unclassified

See 1 more Smart Citation

Detection Techniques for High Dimensional Spatial Multiplexing MIMO System

Lim

The Journal of Korean Institute of Communications and Informati

Choi

2014

“…이러한 문제를 해결하기 위해, 다양한 알고리즘 들이 제안되었다 [8][9][10][11][12][13][14][15] . 특히, Double-Detection [12,13] 과 QR-OSIC with candidates (QOC) [14,15] …”

Section: 모든 가능한 송신 심볼 벡터에 대한 유클리디언unclassified

Low-Complexity Soft-MIMO Detection Algorithm Based on Ordered Parallel Tree-Search Using Efficient Node Insertion

Park

The Journal of Korean Institute of Communications and Informati

2012

This paper proposes an low-complexity soft-output multiple-input multiple-output (soft-MIMO) detection algorithm for achieving soft-output maximum-likelihood (soft-ML) performance under max-log approximation. The proposed algorithm is based on a parallel tree-search (PTS) applying a channel ordering by a sorted-QR decomposition (SQRD) with altered sort order. The empty-set problem that can occur in calculation of log-likelihood ratio (LLR) for each bit is solved by inserting additional nodes at each search level. Since only the closest node is inserted among nodes with opposite bit value to a selected node, the proposed node insertion scheme is very efficient in the perspective of computational complexity. The computational complexity of the proposed algorithm is approximately 37-74% of that of existing algorithms, and from simulation results for a 4×4 system, the proposed algorithm shows a performance degradation of less than 0.1dB. ※ 본 연구는 지식경제부 기술혁신사업(10035389)의 지원을 받아 수행되었습니다.주저자：연세대학교 전기전자공학과 IT-SoC

Circuits Syst Signal Process

“…Focusing on detection methods with a fixed number of visited nodes, in [5,6] the hard-output FSD in [7] was extended to provide soft information by obtaining an improved list of candidates with respect to the one in [15]. Between the two soft-output-FSD proposals, the algorithm shown in [5] achieved good demod- ulation results in a turbo encoded system expanding a lower number of candidates than the one in [6].…”

Section: A U T H O R C O P Ymentioning

confidence: 99%

High-Speed RS(255, 239) Decoder Based on LCC Decoding

García-Herrero

Valls

Meher

2011

Abstract. The use of many-core processors such as general purpose Graphic Processing Units (GPUs) has recently become attractive for the efficient implementation of signal processing algorithms for communication systems. This is due to the costeffectiveness of GPUs together with their potential capability of parallel processing. This paper presents an implementation of the widely employed fixed-complexity sphere decoder on GPUs, which allows to considerably decrease the computational time required for the data detection stage in multiple-input multiple-output systems. Both, the hard-and soft-output versions of the method have been implemented. Speedup results show the proposed GPU implementation boosts the runtime of the parallel execution of the methods in a high performance multi-core CPU. In addition, the throughput of the algorithm is evaluated and is shown to outperform other recent implementations and to fulfill the real-time requirements of several LTE configurations.