How to meet the demand for increasing number of users, higher data rates, and
stringent quality-of-service (QoS) in the beyond fifth-generation (B5G)
networks? Cell-free massive multiple-input multiple-output (MIMO) is considered
as a promising solution, in which many wireless access points cooperate to
jointly serve the users by exploiting coherent signal processing. However,
there are still many unsolved practical issues in cell-free massive MIMO
systems, whereof scalable massive access implementation is one of the most
vital. In this paper, we propose a new framework for structured massive access
in cell-free massive MIMO systems, which comprises one initial access
algorithm, a partial large-scale fading decoding (P-LSFD) strategy, two pilot
assignment schemes, and one fractional power control policy. New closed-form
spectral efficiency (SE) expressions with maximum ratio (MR) combining are
derived. The simulation results show that our proposed framework provides high
SE when using local partial minimum mean-square error (LP-MMSE) and MR
combining. Specifically, the proposed initial access algorithm and pilot
assignment schemes outperform their corresponding benchmarks, P-LSFD achieves
scalability with a negligible performance loss compared to the conventional
optimal large-scale fading decoding (LSFD), and scalable fractional power
control provides a controllable trade-off between user fairness and the average
SE.

本文提出了一种新的结构化大规模接入算法框架，包括一种初始接入算法、一种部分大尺度衰落解码策略、两种导频分配方案和一种分式功率控制策略，模拟结果表明，该框架在局部部分最小均方误差 (LP-MMSE) 和最大比例 (MR) 合并时提供了高的谱效率。