Approaching MIMO channel capacity with reduced-complexity soft sphere decoding

Wang, R.; Giannakis, Georgios B.

doi:10.1109/wcnc.2004.1311795

Cited by 67 publications

(66 citation statements)

References 8 publications

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“…Originally, the MAP hypothesis and the counter hypotheses can be found through repeating the tree search [47] that requires a large computational complexity cost. To overcome this, the single tree-search algorithm [24,25] search the sub-tree originating from a given node if the Euclidean distance leads to an update of either d MAP or at least one of d MAP i,b .…”

Section: Single Tree-search Sphere Decoder (Sts-sd)mentioning

confidence: 99%

Iterative receivers combining MIMO detection with turbo decoding: performance-complexity trade-offs

Chall

Nouvel

Hélard

et al. 2015

J Wireless Com Network

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Recently, iterative receiver combining multiple-input multiple-output (MIMO) detection with channel decoding has been widely considered to achieve near-capacity performance and reliable high data rate transmission, for future wireless communication systems. However, such iterative processing increases the computational complexity at the receiver. In this paper, the computational complexity of MIMO detection algorithms combined with turbo decoding is investigated. We first present an overview of the family of MIMO detection algorithms based on sphere decoding, K-Best decoding, and interference cancellation. A recently proposed low-complexity K-Best decoder (LC-K-Best) is also presented. Moreover, we analyze the convergence of combining these detection algorithms with the turbo decoder using the extrinsic information transfer (EXIT) chart. Consequently, a new scheduling order of the number of iterations for the iterative process is proposed. Several system configurations are developed and compared in terms of performance and complexity. Simulations and analytical results show that the new scheduling provides good performance with a large saving in the complexity. Additionally, the LC-K-Best decoder shows a good performance-complexity tradeoff, and it is therefore suitable for parallel and pipeline architectures that can meet high throughput requirements.

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Section: Single Tree-search Sphere Decoder (Sts-sd)mentioning

confidence: 99%

Iterative receivers combining MIMO detection with turbo decoding: performance-complexity trade-offs

Chall

Nouvel

Hélard

et al. 2015

J Wireless Com Network

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show abstract

“…The STS-SD pruning criterion ensures that a given node and the entire subtree originating from that node are explored only if this could lead to an update of either λ ML or of at least one of the λ ML i,b , which enables significant complexity savings compared to other tree-search based soft-output MIMO detection algorithms, e.g., [10,18].…”

Section: Soft-output Single Tree-search Sphere Decodingmentioning

confidence: 99%

VLSI Implementation of Hard- and Soft-Output Sphere Decoding for Wide-Band MIMO Systems

Studer

Wenk

Burg

2012

VLSI-SoC: Forward-Looking Trends in IC and Systems Design

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Abstract. Multiple-input multiple-output (MIMO) technology in combination with orthogonal frequency-division multiplexing (OFDM) is the key to meet the demands for data rate and link reliability of modern wideband wireless communication systems, such as IEEE 802.11n or 3GPP-LTE. The full potential of such systems can, however, only be achieved by high-performance data-detection algorithms, which typically exhibit prohibitive computational complexity. Hard-output sphere decoding (SD) and soft-output single tree-search (STS) SD are promising means for realizing high-performance MIMO detection and have been demonstrated to enable efficient implementations in practical systems. In this chapter, we consider the design and optimization of register transfer-level implementations of hard-output SD and soft-output STS-SD with minimum area-delay product, which are well-suited for wide-band MIMO systems. We explain in detail the design, implementation, and optimization of VLSI architectures and present corresponding implementation results for 130 nm CMOS technology. The reported implementations significantly outperform the area-delay product of previously reported hard-output SD and soft-output STS-SD implementations.

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“…Each additional tree-search must force the detector to keep one of the bits in x ML fixed. This strategy, which is known as Repeated Tree Search (RTS) [27], is very intuitive but performs several redundant calculations throughout the tree. A more efficient way to calculate the exact max-log-map LLRs without neither listsize constraints nor sphere radius was proposed in [25].…”

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

Circuits Syst Signal Process

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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.

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Approaching MIMO channel capacity with reduced-complexity soft sphere decoding

Cited by 67 publications

References 8 publications

Iterative receivers combining MIMO detection with turbo decoding: performance-complexity trade-offs

Iterative receivers combining MIMO detection with turbo decoding: performance-complexity trade-offs

VLSI Implementation of Hard- and Soft-Output Sphere Decoding for Wide-Band MIMO Systems

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

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