This paper investigates the relay hybrid precoding design in millimeter-wave (mmWave) massive MIMO systems. The optimal design of the relay hybrid precoding is highly nonconvex, due to the six-order polynomial objective function, sixorder polynomial constraint, and constant-modulus constraints. To efficiently solve this challenging non-convex problem, we first reformulate it into three quadratic subproblems, where one of the subproblems is convex and the other two are non-convex. Then, we propose an iterative successive approximation (ISA) algorithm to attain the high-approximate optimal solution to the original problem. Specifically, in the proposed ISA algorithm, we first convert the two non-convex subproblems to convex ones by the relaxation of the constant-modulus constraints, and then we solve the three corresponding convex subproblems iteratively. We theoretically prove that the ISA algorithm converges to a Karush-Kuhn-Tucker (KKT) point of the original problem. Simulation results demonstrate that the proposed ISA algorithm achieves good performance in terms of achievable rate in both fullconnected and sub-connected relay hybrid precoding systems.

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This paper investigates the hybrid precoding design in millimeter-wave (mmWave) systems with a fully-adaptive-connected precoding structure, where a switch-controlled connection is deployed between every antenna and every radio frequency (RF) chain. To maximally enhance the energy efficiency (EE) of hybrid precoding under this structure, the joint optimization of switch-controlled connections and the hybrid precoders is formulated as a large-scale mixed-integer non-convex problem with highdimensional power constraints. To efficiently solve such a challenging problem, we first decouple it into a continuous hybrid precoding (CHP) subproblem. Then, with the hybrid precoder obtained from the CHP subproblem, the original problem can be equivalently reformulated as a discrete connection-state (DCS) problem with only 0-1 integer variables. For the CHP subproblem, we propose an alternating hybrid precoding (AHP) algorithm. Then, with the hybrid precoder provided by the AHP algorithm, we develop a matching assisted fully-adaptive hybrid precoding (MA-FAHP) algorithm to solve the DCS problem. It is theoretically shown that the proposed MA-FAHP algorithm always converges to a stable solution with the polynomial complexity. Finally, simulation results demonstrate that the superior performance of the proposed MA-FAHP algorithm in terms of EE and beampattern. Index TermsMillimeter wave, massive MIMO, hybrid precoding, energy efficiency This paper was partially presented at the IEEE ICC 2019 [1].

This paper proposes a novel design of cooperative non-orthogonal layered multicast multiple access in a heterogeneous network, where the information is encoded into the messages of high-priority (HP) and low-priority (LP). Two types of multicast users coexist in the network: 1) regular users (RUs), which are located far away from the base-station (BS) and expect to decode only the HP message (due to the weak channels); 2) advanced users (AUs), which are located close to the BS and expect to decode both HP and LP messages. To improve the reliability of layered multicast, we consider that the successful AUs (those AUs who successfully decode the HP and LP messages) serve as potential relays to assist other AUs/RUs. Based on this idea, two novel cooperation strategies are proposed for different cases of channel information availability. For each proposed strategy, we derive closed-form exact outage probabilities of AUs and RUs, and then further analyze their diversity orders. Moreover, considering that the layered multicast is outage-constrained, we theoretically evaluate the energy consumption of both strategies and demonstrate their energy saving gains over the direct nonorthogonal multiple access for layered multicast. Finally, our theoretical analysis is verified by numerical results, and the advantages of the proposed strategies are also demonstrated.

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