Mohammad NaseriTehrani

Mohammad NaseriTehrani, MohammadJavad Salehi, Antti Tölli

Subpacketization remains a major obstacle to the practical deployment of coded caching (CC) in multi-antenna wireless networks. In this paper, we propose a low-complexity multiple-input multiple-output (MIMO) CC scheme that enables flexible delivery rate adaptation while substantially reducing subpacketization requirements. The proposed design builds on a virtual decomposition of the broadcast channel and extends the shared-cache model to multi-antenna receivers, enabling adaptive selection of feasible user and stream configurations and thereby providing explicit control over the spatial multiplexing gain under linear decodability constraints. Analytical results show that the proposed framework can asymptotically approach the best-known achievable degrees of freedom (DoF) under linear decodability constraints while requiring orders-of-magnitude lower subpacketization than existing schemes. Numerical evaluations further demonstrate that this flexibility yields notable throughput improvements at practical signal-to-noise ratios.

Mohammad NaseriTehrani, MohammadJavad Salehi, Antti Tölli

This is an extended journal version of the conference paper published in ISIT 2025; submitted to IEEE Transactions on Communications (TCOM). Integrating coded caching (CC) into multiple-input multiple-output (MIMO) communications significantly enhances the achievable degrees of freedom (DoF). This paper investigates a practical cache-aided asymmetric MIMO configuration with cache ratio $γ$, where a server with $L$ transmit antennas communicates with $K$ users. The users are partitioned into $J$ groups, and each user in group $j$ has $G_j$ receive antennas. We propose four content-aware MIMO-CC strategies: \emph{min-$G$} enforces symmetry using the smallest antenna count among users; \emph{Grouping} maximizes intra-subset spatial multiplexing gain at the expense of some global caching gain; \emph{Super-grouping} aggregates users into optimized \emph{min-$G$}-based super-sets with identical effective receive multiplexing gains before applying \emph{Grouping} across them; and \emph{Phantom} redistributes spatial resources assuming ``phantom'' antennas at the users to bridge the performance gains of \emph{min-$G$} and \emph{Grouping}. We develop these asymmetric strategies under three reference symmetric CC placement-delivery policies with guaranteed linear decodability: a DoF-optimal policy achieving the optimal single-shot DoF, and two closed-form policies, namely combinatorial and linear cyclic low-complexity constructions, with the cyclic policy attaining DoF performance close to the others in many operating regimes. Analytical and numerical results demonstrate significant DoF improvements across various system configurations, and that policy-strategy combinations offer flexible trade-offs between DoF and subpacketization complexity.

Mohammad NaseriTehrani, MohammadJavad Salehi, Antti Tölli

Coded caching (CC) can transform cache memory at network devices into an active communication resource. Prior studies have shown that CC can significantly enhance the achievable Degrees of Freedom (DoF) in multi-input multi-output (MIMO) systems. To fully exploit MIMO-CC gains across all SNR regimes and enable practical linear receivers, flexible scheduling is required. Existing DoF analysis, scheduling, and linear receiver design, however, largely assume symmetric stream allocations across users. This paper extends the authors' recent work on DoF and linear decodability analysis for MIMO-CC systems by deriving a simple criterion, based on per-user stream allocation, that guarantees linear decodability for both symmetric and non-symmetric bit-level CC schemes. Building on this, we propose a heuristic MIMO-CC delivery and scheduling framework that enables asymmetric stream allocation while adhering to linear decodability, thereby expanding the feasibility region of achievable DoF compared to symmetric-constrained designs.