Relaxed-Bound K-Best Sphere Detection for Differential Unitary Space-Time Modulation
Du, Yipeng; Han, Shuangshuang; Liu, Jian; Zhang, Yinghua
2017
Conference Name2017 The Ninth International Conference on Wireless Communications and Signal Processing
Conference Date2017-10-11
Conference PlaceNanjing, China
AbstractLarge scale multiple input multiple output (MIMO), commonly referred to as massive MIMO, is one of the most important physical layer disruptions in network evolution that would lead to significant increase in spectral and energy efficiency envisioned for 5G networks. However, the computational complexity of massive MIMO system becomes the key problem for its practical implementation. As known, Differential Unitary Space-Time Modulation (DUSTM) has been proposed as an efficient modulation choice for such MIMO transmissions where channel state information (CSI) is not required at the receiver. However, traditional DUSTM implementation relies mainly on Maximum Likelihood Detection (MLD) achieving optimal performance, which is not easily compatible with massive MIMO systems due to its exponentially increasing complexity with increasing number of transmitting and receiving antennas. Therefore, in this paper, in order to overcome the aforementioned disadvantages, we propose a new detection algorithm named RelaxedBound K-Best Sphere Detection (RBKSD). Compared to the traditional K-Best Sphere Detection (KSD) algorithm, the main idea of our algorithm is to relax the bound K of the conventional KSD to be K + Γ, thereby achieving quasioptimal performance with significantly reduced computational complexity. Simulation results confirm that the proposed RBKSD algorithm shows superior performance and reduced complexity compared to other notable schemes such as MLD, traditional sphere detection algorithm and the KSD.
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15303
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
Recommended Citation
GB/T 7714
Du, Yipeng,Han, Shuangshuang,Liu, Jian,et al. Relaxed-Bound K-Best Sphere Detection for Differential Unitary Space-Time Modulation[C],2017.
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