This work presents a first comprehensive analysis of the impact of vector coded caching (VCC) in multi-user multiple-input multiple-output (MU-MIMO) systems with multiple receive antennas and variable pathloss -- two key factors that critically influence systems with inherent MU unicasting behavior. We investigate two widely adopted precoding strategies: (i) blockdiagonalization (BD) at the transmitter combined with maximal ratio combining (MRC) at the receivers, and (ii) zero-forcing (ZF) precoding. Our analysis explicitly accounts for practical considerations such as channel fading, channel state information (CSI) acquisition overhead, and fairness-oriented power allocation. Our contributions span both analytical and simulation-based fronts. On the analytical side, we derive analytical expressions for the achievable throughput under BD-MRC and ZF, highlighting the performance benefits of equipping multi-antenna users with cache-aided interference management. Specifically, we develop a low-complexity BD-MRC optimization method that leverages matrix structure to significantly reduce the dimensionality involved in precoding computation, followed by solving the associated maxmin fairness problem through an efficient one-dimensional search. In the massive MIMO regime, an asymptotic expression for the achievable throughput over Rayleigh fading channels is also derived. Simulations validate our theoretical results, confirming that VCC delivers substantial performance gains over optimized cacheless MU-MIMO systems. For example, with 32 transmit antennas and 2 receive antennas per user, VCC yields throughput improvements exceeding 300%. These gains are further amplified under imperfect CSI at the transmitter, where VCC's ability to offload interference mitigation to the receivers ensures robust performance even in the face of degraded CSI quality and elevated acquisition costs.

翻译：本文首次全面分析了向量编码缓存在配备多接收天线且存在可变路径损耗的多用户多输入多输出系统中的影响——这两个关键因素对具有固有多用户单播行为的系统至关重要。我们研究了两种广泛采用的预编码策略：发射机端的块对角化结合接收机端的最大比合并，以及迫零预编码。我们的分析明确考虑了实际因素，如信道衰落、信道状态信息获取开销以及面向公平性的功率分配。我们的贡献涵盖解析与仿真两个方面。在解析方面，我们推导了块对角化-最大比合并与迫零方案下可达吞吐量的解析表达式，阐明了为多天线用户配备缓存辅助干扰管理所带来的性能优势。具体而言，我们提出了一种低复杂度的块对角化-最大比合并优化方法，该方法利用矩阵结构显著降低预编码计算涉及的维度，随后通过高效的一维搜索解决相关的最大最小公平性问题。在大规模多输入多输出场景下，我们还推导了瑞利衰落信道上可达吞吐量的渐近表达式。仿真验证了我们的理论结果，证实向量编码缓存相比经过优化的无缓存多用户多输入多输出系统能带来显著的性能增益。例如，在配备32根发射天线且每用户配备2根接收天线时，向量编码缓存可实现超过300%的吞吐量提升。在发射机信道状态信息不完美的条件下，这些增益进一步放大，因为向量编码缓存将干扰抑制任务卸载至接收机的能力确保了即使在信道状态信息质量下降且获取成本升高的情况下，系统仍能保持稳健性能。