Energy-Efficient 5G Outdoor-to-Indoor Communication: SUDAS Over Licensed and Unlicensed Spectrum

TL;DR

This paper introduces a resource allocation algorithm for 5G outdoor-to-indoor communication using SUDAS, which leverages licensed and unlicensed spectrum to enhance energy and spectral efficiency for single-antenna UEs.

Contribution

It proposes a novel joint resource allocation method for SUDAS that maximizes energy efficiency by combining licensed and unlicensed bands, with tractable optimization solutions.

Findings

Significant energy efficiency gains over baseline systems.

Effective utilization of licensed and unlicensed spectrum for parallel data streams.

Optimal precoding and post-processing matrices diagonalize the channel.

Abstract

In this paper, we study the joint resource allocation algorithm design for downlink and uplink multicarrier transmission assisted by a shared user equipment (UE)-side distributed antenna system (SUDAS). The proposed SUDAS simultaneously utilizes licensed frequency bands and unlicensed frequency bands, (e.g. millimeter wave bands), to enable a spatial multiplexing gain for single-antenna UEs to improve energy efficiency and system throughput of $5$-th generation (5G) outdoor-to-indoor communication. The design of the UE selection, the time allocation to uplink and downlink, and the transceiver processing matrix is formulated as a non-convex optimization problem for the maximization of the end-to-end system energy efficiency (bits/Joule). The proposed problem formulation takes into account minimum data rate requirements for delay sensitive UEs and the circuit power consumption of all transceivers. In order to design a tractable resource allocation algorithm, we first show that the optimal transmitter precoding and receiver post-processing matrices jointly diagonalize the end-to-end communication channel for both downlink and uplink communication via SUDAS. Subsequently, the matrix optimization problem is converted to an equivalent scalar optimization problem for multiple parallel channels, which is solved by an asymptotically globally optimal iterative algorithm. Besides, we propose a suboptimal algorithm which finds a locally optimal solution of the non-convex optimization problem. Simulation results illustrate that the proposed resource allocation algorithms for SUDAS achieve a significant performance gain in terms of system energy efficiency and spectral efficiency compared to conventional baseline systems by offering multiple parallel data streams for single-antenna UEs.