Optimal Backhaul Resource Allocation with User Pairing in Uplink Coordinated Multicarrier Networks

Gao, Yuan; Ao, Hong; Zhou, Quan; Chu, Jian; Zhou, Bo; Zhou, Weigui; Li, Yang

doi:10.1109/iiki.2015.44

Cited by 1 publication

(1 citation statement)

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“…The system level simulation platform supports the multi-users, multi-base stations scenario, which could reflect the performance of our proposed algorithm in a real scenario. References for our simulation platform can be found in [ 37 , 38 ].…”

Section: Simulation and Analysismentioning

confidence: 99%

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

Gao

Zhou

et al. 2016

Sensors

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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.

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Section: Simulation and Analysismentioning

confidence: 99%