A Novel Optimal Joint Resource Allocation Method in Cooperative Multicarrier Networks: Theory and Practice

Sensors

Peng Xue¹  Yi Li¹  Jian Chu²  Weigui Zhou²  Bo Zhou²  Hong Ao²  Yuan Gao²  Kang Wang²  Quan Zhou² 

[1] State Key Laboratory on Microwave and Digital Communications, National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084, China;Xichang Satellite Launch Center, Xichang 615000, China;

关键词: distributed compression;    backhaul optimization;    user pairing;    uplink CoMP;    virtual MIMO;   

DOI  :  10.3390/s16040522

来源: DOAJ

【 摘 要 】

With the increasing demands for better transmission speed and robust quality of service (QoS), the capacity constrained backhaul gradually becomes a bottleneck in cooperative wireless networks, e.g., in the Internet of Things (IoT) scenario in joint processing mode of LTE-Advanced Pro. This paper focuses on resource allocation within capacity constrained backhaul in uplink cooperative wireless networks, where two base stations (BSs) equipped with single antennae serve multiple single-antennae users via multi-carrier transmission mode. In this work, we propose a novel cooperative transmission scheme based on compress-and-forward with user pairing to solve the joint mixed integer programming problem. To maximize the system capacity under the limited backhaul, we formulate the joint optimization problem of user sorting, subcarrier mapping and backhaul resource sharing among different pairs (subcarriers for users). A novel robust and efficient centralized algorithm based on alternating optimization strategy and perfect mapping is proposed. Simulations show that our novel method can improve the system capacity significantly under the constraint of the backhaul resource compared with the blind alternatives.

【 授权许可】

Unknown