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arXiv 2501.13380cs.ITmath.IT

预编码大规模MIMO信道的联合功率与比特分配

Joint Power and Bit Allocation for Precoded Massive MIMO Channels

Shuiyin Liu, Amin Sakzad

AI总结:

针对预编码大规模MIMO系统的功率与比特分配联合优化问题,提出自适应QAM方案,将MWF简化为经典WF,预计算QAM配置以截断SVD替代完整SVD,实现低复杂度与更优解码性能。

摘要:

本研究针对采用离散输入字母表(尤其是QAM星座)的预编码大规模n×n MIMO系统,解决功率与比特分配的联合优化问题。我们提出一种自适应QAM方案,在给定n时保持与高斯输入容量的固定差距。关键发现是,在该方案下,汞/注水(MWF)解可解析简化为经典注水(WF)策略。此外,在大系统假设下,自适应QAM配置可预计算,从而能用截断SVD替代完整SVD,实现显著计算节省。为支持实际部署,我们开发了一种比特分配算法,在满足目标传输数据率的同时最小化整体解码错误率,并将计算复杂度保持在O(n log n)。仿真结果证实,所提截断SVD预编码结合联合功率与比特分配,相较于传统方法,解码性能更优且复杂度显著降低。

英文摘要:

This work addresses the joint optimization of power and bit allocation in precoded large-scale n x n MIMO systems with discrete input alphabets, specifically QAM constellations. We propose an adaptive QAM scheme that maintains a fixed gap to the Gaussian-input capacity for a given n. A key finding is that, under the proposed scheme, the mercury/waterfilling (MWF) solution reduces analytically to the classical water-filling (WF) policy. Furthermore, the adaptive QAM configuration can be precomputed under the large-system assumption, enabling the replacement of full SVD with truncated SVD and yielding substantial computational savings. To support practical deployment, we develop a bit-allocation algorithm that meets a target transmission data rate while minimizing the overall decoding error rate and preserving computational complexity at O(n log n). Simulation results confirm that the proposed truncated SVD precoding, paired with the joint power and bit allocation, achieves superior decoding performance relative to conventional approaches, while operating at significantly lower complexity.

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