In order to support colourful multimedia services with strict quality-of-service (QoS) requirements of user equipments (UEs), the space-air-ground integrated networks (SAGIN) can be taken as a promising approach to enhance network capacity. Among them, millimeter wave (mmWave) and edge caching promise to significantly improve the SAGIN performance due to the advantage in rich bandwidth resource and low latency, respectively. In this paper, we investigate the joint caching and resource allocation for multimedia services in SAGIN, where multimedia content requests can be simultaneously served by multiple access points (APs). Considering the delay-constraint of multimedia services, we then formulate a mixed-integer non-linear programming (MINLP) problem aiming at minimizing the service delay, which involves jointly optimizing coded caching (CC), power allocation (PA) and UEs-to-APs association (UA). We propose to find the optimal solution by employing an alternating iteration optimization framework. The optimal CC and PA problems are firstly addressed by utilizing convex optimization technology. Then, two many-to-many swap matching algorithms are developed to slove the UA subproblem effectively. Numerical results demonstrate that our proposed algorithms can substantially reduce the service delay over other benchmarks.

With the development of millions more small-cell base stations (SBSs) and billions of connected devices in the future wireless networks, the need for energy-efficient system design and operation will be even more compelling. This paper investigates the content caching, resource allocation and energy cooperation in coded cache enabled heterogeneous networks (HetNets), where SBSs with cache ability are powered by both conventional grids and renewable energy sources, and energy can be shared among SBSs via the smart grid. We formulate the joint optimization problem, aims at minimizing the conventional grid energy consumption while satisfying quality of service (QoS) requirements of users. To deal with the mixed integer nonlinear optimization problem, the original problem is decomposed into three lower level problems, i.e., content caching, content delivery and energy cooperation. We first propose an alternative iterative algorithm to optimize content caching and content delivery by jointly applying convex optimization techniques and matching theory. Then, by discussing two representative energy cooperative scenarios of smart grid supported networks, we propose efficient energy cooperation algorithms for the two scenarios, respectively. Furthermore, the joint content caching, content delivery and energy cooperation optimization algorithms are developed to minimize the conventional grid energy consumption in the considered HetNets. Simulation results demonstrate that the joint algorithms can significantly reduce the conventional grid energy consumption compared with other benchmarks.

This paper considers the hybrid precoder design in millimeter wave (mmWave) multi-input multi-output (MIMO) systems with low-resolution analog phase shifters. Aiming at reducing the complexities of the near-optimal algorithms, we propose a low-complexity multi-user hybrid precoding scheme based on tree-coding-aided adaptive-cross-entroy (TC-ACE) algorithm. By defining some discrete variables for the analog precoders and combiners, the problem of hybrid precoding is transformed into a cross-entroy (CE) optimization problem, which can be solved by iteratively updating the probability distributions of the predefined discrete variables. In order to derive the closed-form expression of the probability distributions, tree-coding is used to encode each entry of the analog precoders and combiners with a binary number. Through iterations, optimal analog precoders and combiners will be obtained when its probabilities are sufficiently high. Simulation results show that when the number of users exceeds a certain value, the proposed scheme outperforms the alternating minimization algorithm and coordinate descent method in terms of both the sum-rate and complexity.

Millimeter wave (mmWave) frequencies with rich bandwidth can greatly alleviate the surging traffic demand of wireless communication from mobile video streaming. However, the harsh propagation environment at mmWave bands and user mobility make it hard to provide a reliable service. Multibeam transmissions can be taken as an essential approach for maintaining a robust mmWave link. Meanwhile, the introduction of coded caching can further reduce the end-to-end latency and backhaul traffic. Considering the interaction between caching and transmission in mobility scenario, we develop a joint design for mmWave heterogeneous networks (HetNets), by combining multibeam transmission and maximum distance separable (MDS)-coded caching. First, a joint optimization problem of cache placement and beam pair selection is formulated, in order to maximize the backhaul traffic offload in mmWave HetNets. To solve the mixed-timescale mixed-integer nonlinear programming (MINLP) problem, we then decompose the joint problem into the long-term mobility-based proactive content caching (CC) and short-term content delivery (CD) subproblems. Subsequently, two many-to-many matching-based algorithms are proposed for tackling the CD subproblem and the convex technique is applied to deal with the CC subproblem. Simulation results demonstrate the efficacy of the proposed algorithms over benchmark schemes.