Software defined radio implementation of K-best list sphere detector algorithm

Janhunen, Janne; Silvén, Olli; Juntti, Markku; Myllyla, M.

doi:10.1109/icsamos.2008.4664852

Cited by 10 publications

(6 citation statements)

References 13 publications

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“…Because of many differences, such as provided flexibility, BER performance, technology or accuracy of estimations, a fair quantitative comparison with work in literature is difficult. Nevertheless, the following overview gives an idea about the efficiency of related implementations: The references [1,4,8,15,16] are based on simple linear hard-output detection. Although the complexity of linear hard-output detection is much lower compared to near-ML soft-output detection, the implementation of [16] consumes about 1 mW power while offering less than 50 Mbps throughput for 2 × 2 64-QAM.…”

Section: Comparisonmentioning

confidence: 99%

“…Nevertheless, the following overview gives an idea about the efficiency of related implementations: The references [1,4,8,15,16] are based on simple linear hard-output detection. Although the complexity of linear hard-output detection is much lower compared to near-ML soft-output detection, the implementation of [16] consumes about 1 mW power while offering less than 50 Mbps throughput for 2 × 2 64-QAM. Reference [32] implements a near-ML hard-output detector on a Nvidia 9600GT floatingpoint Graphical Processor Unit (GPU), which includes 64 streams processors and 512MB DDR3 memory.…”

Section: Comparisonmentioning

confidence: 99%

“…The references [4,31] demonstrate MIMO processing, but based on simple linear detection, which does not enable to fully exploit the potential of MIMO technology [13]. The implementation of MIMO processing on a Sandblaster processor in [16] does not include the computational dominant soft-output computation. Wu et al [33] demonstrates advanced MIMO processing on a floating-point Graphics Processing Unit (GPU).…”

Section: Introductionmentioning

confidence: 98%

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Exploration of Soft-Output MIMO Detector Implementations on Massive Parallel Processors

Fasthuber

Novo

et al. 2010

J Sign Process Syst

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Emerging Software Defined Radio (SDR) baseband platforms are based on multiple processors with massive parallelism. Although the computational power of these platforms would theoretically enable SDR solutions with advanced wireless signal processing, existing work implements still rather basic algorithms. For instance, current Multiple-Input Multiple-Output (MIMO) detector implementations are typically based on simple linear hard-output and not on advanced near-Maximum Likelihood (ML) soft-output detection. However, only the latter enables to exploit the full potential of MIMO technology. In this work, we explore the feasibility of advanced soft-output near-ML MIMO detectors on massive parallel processors. Although such detectors are considered to be very challenging due to their high computational complexity, we combine architecture-friendly algorithm design, application

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Section: Comparisonmentioning

confidence: 99%

Section: Comparisonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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Exploration of Soft-Output MIMO Detector Implementations on Massive Parallel Processors

Fasthuber

Novo

et al. 2010

J Sign Process Syst

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“…Esse tema tem sido frequentemente debatido ao nível mundial entre os profissionais da saúde, em particular a área de enfermagem, sugerindo que as equipes de saúde não estão familiarizadas com a presença da família/acompanhantes nos procedimentos de emergência. 17,18 Embora alguns estudos demonstrem que equipes de enfermagem tem mais proximidade e diálogo com familiares das crianças hospitalizadas, assim como nos setores de urgência e emergência pediátrica. [6][7][8]17,18 As participantes apontam que a dificuldade mais complexa é a condição de entrada da criança no atendimento de emergência, seja em relação à gravidade do quadro, ou em relação à questão emocional.…”

Section: Introductionunclassified

Percepções E Significados Sobre O Atendimento De Crianças Em Situação De Emergência

Barreto

Silva

Rocha

et al. 2021

Rev Enferm Atenção Saúde

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Objetivo: Conhecer as percepções da equipe enfermagem de um Pronto Socorro infantil sobre o atendimento à criança em situação de emergencial. Método: Estudo de abordagem qualitativa, descritiva. O cenário de coleta de dado foi uma Unidade de Pronto Socorro Infantil de um hospital de ensino localizado no estado de Minas Gerais com membros da equipe de enfermagem, entrevistados por meio de um questionário semiestruturado. Os dados foram analisados utilizando-se a técnica de análise de conteúdo. Resultados: Participaram do estudo 10 profissionais de enfermagem, todos do sexo feminino, sendo duas enfermeiras e oito técnicas de enfermagem, foram identificadas percepções e significados sobre o conhecimento, a responsabilidade, as dificuldades, as necessidades de protocolos e as formas de aprendizagem do atendimento. Conclusão: Constatou-se que o conhecimento, a prática, a responsabilidade, a habilidade e a comunicação são fatores que possibilitam uma assistência segura à criança e seus familiares em situação de urgência e emergência.

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“…For example, due to the limited amount of resource on GPU, such as on-chip memory and/or long latency due to software sorting [7], many existing algorithms such as depth first sphere detector and Kbest detector do not map very efficiently onto this architecture. Furthermore, designing a detection algorithm that scales well, keeping the cores fully utilized to achieve peak throughput across different combinations of number of antennas and different modulation, is a difficult task.…”

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confidence: 99%

A GPU implementation of a real-time MIMO detector

Gupta

Sun

et al. 2009

2009 IEEE Workshop on Signal Processing Systems

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Abstract-Multiple-input multiple-output (MIMO) is an existing technique that can significantly increase throughput of the system by employing multiple antennas at the transmitter and the receiver. Realizing maximum benefit from this technique requires computationally intensive detectors which poses significant challenges to receiver design. Furthermore, a flexible detector or multiple detectors are needed to handle different configurations. Graphical Processor Unit (GPU), a highly parallel commodity programmable co-processor, can deliver extremely high computation throughput and is well suited for signal processing applications. However, careful architecture aware design is needed to leverage performance offered by GPU. We show we can achieve good performance while maintaining flexibility by employing an optimized trellis-based MIMO detector on GPU.

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Software defined radio implementation of K-best list sphere detector algorithm

Cited by 10 publications

References 13 publications

Exploration of Soft-Output MIMO Detector Implementations on Massive Parallel Processors

Exploration of Soft-Output MIMO Detector Implementations on Massive Parallel Processors

Percepções E Significados Sobre O Atendimento De Crianças Em Situação De Emergência

A GPU implementation of a real-time MIMO detector

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