Gao Yuan, Zhou Weigui, Ao Hong, Chu Jian, Zhou Quan, Zhou Bo, Wang Kang, Li Yi, Xue Peng
Xichang Satellite Launch Center, Xichang 615000, China.
State Key Laboratory on Microwave and Digital Communications, National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084, China.
Sensors (Basel). 2016 Apr 12;16(4):522. doi: 10.3390/s16040522.
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.
随着对更高传输速度和强大服务质量（QoS）需求的不断增加，容量受限的回程链路逐渐成为协作无线网络中的瓶颈，例如在长期演进技术高级版（LTE-Advanced Pro）联合处理模式下的物联网（IoT）场景中。本文聚焦于上行链路协作无线网络中容量受限回程链路内的资源分配，其中两个配备单天线的基站通过多载波传输模式为多个单天线用户提供服务。在这项工作中，我们提出了一种基于压缩转发和用户配对的新型协作传输方案，以解决联合混合整数规划问题。为了在有限回程链路条件下最大化系统容量，我们制定了用户排序、子载波映射以及不同用户对（用户的子载波）之间回程链路资源共享的联合优化问题。提出了一种基于交替优化策略和完美映射的新型鲁棒且高效的集中式算法。仿真结果表明，与盲目选择的方法相比，我们的新方法在回程链路资源受限的情况下能够显著提高系统容量。
