利用因子图增强OFDM系统的数据检测

Jinda Yang, Qinghua Guo, D. Huang, S. Nordholm
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引用次数: 1

摘要

在OFDM系统中,循环前缀(CP)消除了块间干扰,并允许在接收端使用计算效率高的单抽头均衡器。虽然造成频谱效率和功率效率的损失,但CP带来了可用于检测的数据的额外信息。因此,本文没有像传统的OFDM系统那样丢弃CP,而是利用前缀冗余并将其应用于turbo均衡系统的软输入软输出均衡器中。利用因子图,提出了一种均衡算法,通过适当的近似,将算法的复杂度降低到每个数据符号0 (2Rlog2N + 4RG/N log2G + 2RG/N),迭代R次,其中N为块长度,G等于P + L - 1,其中P为CP长度,L为信道长度。仿真结果表明,该均衡系统在2次迭代内收敛,与传统均衡方法相比,该均衡方法获得了显著的增益。
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Enhanced data detection in OFDM systems using factor graph
In OFDM systems, the cyclic prefix (CP) eliminates the interblock interference and enables the use of the computationally efficient single-tap equalizers at the receiver. While posing a loss in both spectrum efficiency and power efficiency, the CP brings extra information about the data which can be used for detection. Therefore, instead of discarding the CP as in the conventional OFDM systems, this paper takes advantage of the prefix redundancy and utilizes it in the soft-input soft-output equalizer of a turbo equalization system. By using factor graph, an equalization algorithm is developed, and with proper approximation, the complexity of the proposed algorithm is reduced to O(2Rlog2N + 4RG/N log2G + 2RG/N) per data symbol for R iterations, where N is the length of the block and G is equal to P + L - 1 with P the CP length and L the channel length. Simulation results show that the turbo equalization system converges within two iterations and the proposed equalization approach achieves significant gain compared to the conventional approach.
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