Due to the high complexity of the pairwise decoding algorithm and the poor performance of zero forcing（ ZF） /minimum mean square error（ MMSE） decoding algorithm, two low-complexity suboptimal decoding algorithms, ...
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Due to the high complexity of the pairwise decoding algorithm and the poor performance of zero forcing（ ZF） /minimum mean square error（ MMSE） decoding algorithm, two low-complexity suboptimal decoding algorithms, called pairwisequasi-ZF and pairwise-quasi-MMSE decoders, are proposed. First,two transmit signals are detected by the quasi-ZF or the quasiMMSE algorithm at the receiver. Then, the two detected signals as the decoding results are substituted into the two pairwise decoding algorithm expressions to detect the other two transmit signals. The bit error rate（ BER） performance of the proposed algorithms is compared with that of the current known decoding ***, the number of calculations of ZF, MMSE, quasi-ZF and quasi-MMSE algorithms is compared with each other. Simulation results showthat the BER performance of the proposed algorithms is substantially improved in comparison to the quasi-ZF and quasiMMSE algorithms. The BER performance of the pairwise-quasiZF（ pairwise-quasi-MMSE） decoder is equivalent to the pairwiseZF（ pairwise-MMSE） decoder, while the computational complexity is significantly reduced.
针对28GHz车联网中车对基础设施(Vehicle-to-Infrastructure,V2I)毫米波信道,开展了准平稳区间的研究.首先,分析了信道准平稳区间的理论基础和计算方法.其次,利用功率相关(Correlation of Power,CP)算法和谱散度(Spectral Divergence,SD...
详细信息
针对28GHz车联网中车对基础设施(Vehicle-to-Infrastructure,V2I)毫米波信道,开展了准平稳区间的研究.首先,分析了信道准平稳区间的理论基础和计算方法.其次,利用功率相关(Correlation of Power,CP)算法和谱散度(Spectral Divergence,SD)算法进行准平稳区间的计算.结果表明,CP算法复杂度低且精度较高,更适合用于计算V2I通信场景下的准平稳区间.最后,利用CP算法计算出的准平稳区间作为新的采样间隔,从而减少了射线跟踪仿真器的采样点数.通过原始采样和减少采样点后的信道特性的比较,在合理的门限值下,利用信道准平稳区间的方法加速了射线跟踪仿真器,并且不会造成信道参数的失真.另外,对于信道特性的分析结果也对车联网在毫米波频段的仿真和设计具有重要意义.
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