This paper investigates the energy efficiency (EE) and spectral efficiency (SE) trade-off in uplink distributed massive multiple-input multiple-output (D-mMIMO) systems. Unlike conventional approaches where power consumption focuses primarily on transmit power, we use a comprehensive system-level power consumption framework which incorporates consumption due to fronthaul signaling, distributed processing, and circuit level power, which are, themselves, critically influenced by the dynamic access point (AP) activation (ON-/OFF decisions), and AP-user equipment (UE) association strategies. Consequently, we analyze the EE-SE trade-off through the joint optimization of transmit power allocation, AP activation, and AP-UE association. We formulate an optimization problem that maximizes EE while satisfying sum-SE constraints, per-user minimum SE requirements, and fronthaul capacity limits. Our solution uses a fractional programming-based approach to simultaneously determine transmit power levels, dynamic AP-UE associations, and AP activation strategies. Numerical results demonstrate that dynamic AP activation and association substantially impact the EE-SE trade-off, revealing optimal operating points that balance spectral performance with energy consumption. The findings provide practical guidelines for energyefficient D-mMIMO deployment in next generation wireless networks, highlighting the importance of adaptive resource allocation in achieving sustainable high-performance communications.

翻译：本文研究了上行链路分布式大规模多输入多输出（D-mMIMO）系统中的能量效率（EE）与频谱效率（SE）权衡问题。与传统方法主要关注发射功率不同，我们采用了一个全面的系统级功耗框架，该框架包含了由前传信令、分布式处理和电路级功耗引起的能耗，而这些能耗本身又受到动态接入点（AP）激活（开启/关闭决策）以及AP-用户设备（UE）关联策略的关键影响。因此，我们通过联合优化发射功率分配、AP激活和AP-UE关联来分析EE-SE权衡。我们构建了一个优化问题，在满足总SE约束、每用户最低SE要求以及前传容量限制的前提下最大化EE。我们的解决方案采用基于分数规划的方法，同时确定发射功率水平、动态AP-UE关联和AP激活策略。数值结果表明，动态AP激活与关联显著影响EE-SE权衡，揭示了平衡频谱性能与能耗的最佳工作点。这些发现为下一代无线网络中能效优化的D-mMIMO部署提供了实用指导，强调了自适应资源分配对于实现可持续高性能通信的重要性。