Enhanced Achievable DoF Bounds for Cache-Aided MIMO Communication Systems

Integrating coded caching (CC) into multiple-input multiple-output (MIMO) communications may significantly enhance the achievable degrees of freedom (DoF) of the wireless networks. In this paper, we consider a cache-aided MIMO configuration with a CC gain $t$, where a server with $L$ Tx antennas communicates with $K$ users, each with $G$ Rx antennas. In the proposed content-aware MIMO strategy, we carefully adjust the number of users $\Omega$ and the number of parallel streams decoded by each user $\beta$ served in each transmission to maximize the DoF. As a result, we achieve a DoF of ${\max_{\beta, \Omega }}{\Omega \beta}$, where ${\beta \le \mathrm{min}\big(G,\frac{L \binom{\Omega-1}{t}}{1 + (\Omega - t-1)\binom{\Omega-1}{t}}\big)}$. To prove the achievability of the proposed DoF bound, we provide a novel transmission strategy based on the simultaneous unicasting of multiple data streams. In this strategy, the missing data packets are scheduled such that the number of parallel streams per transmission is maximized while the decodability of all useful terms by each target user is guaranteed. Numerical simulations validate the findings, confirming the enhanced DoF and improved performance of the proposed design.

Low-complexity Linear Multicast Beamforming for Cache-aided MIMO Communications

A practical and scalable multicast beamformer design in multi-input multi-output~(MIMO) coded caching~(CC) systems is introduced in this paper. The proposed approach allows multicast transmission to multiple groups with partially overlapping user sets using receiver dimensions to distinguish between different group-specific streams. Additionally, it provides flexibility in accommodating various parameter configurations of the MIMO-CC setup and overcomes practical limitations, such as the requirement to use successive interference cancellation~(SIC) at the receiver, while achieving the same degrees-of-freedom~(DoF). To evaluate the proposed scheme, we define the symmetric rate as the sum rate of the partially overlapping streams received per user, comprising a linear multistream multicast transmission vector and the linear minimum mean square error~(LMMSE) receiver. The resulting non-convex symmetric rate maximization problem is solved using alternative optimization and successive convex approximation~(SCA). Moreover, a fast iterative Lagrangian-based algorithm is developed, significantly reducing the computational overhead compared to previous designs. The effectiveness of our proposed method is demonstrated by extensive simulations.