论文标题
共同用户配对的低复杂框架和5G和蜂窝网络以外的合作NOMA的功率控制
A Low-Complexity Framework for Joint User Pairing and Power Control for Cooperative NOMA in 5G and Beyond Cellular Networks
论文作者
论文摘要
本文研究了在细胞下行链路系统中合作非正交多访问(C-NOMA)的性能。系统模型由一个为多个用户提供服务的基站(BS),在该基础站中,具有良好频道质量的用户可以通过半双链(HD)或全双工(FD)设备到设备到设备(D2D)通信之间的BS和频道质量较差的用户之间的传播。我们制定并解决了一个新颖的优化问题,该问题共同确定了最佳的D2D用户配对和最佳功率控制方案,该方案的目标是最大化整个系统的可实现的总和率,同时保证所有用户的一定服务质量(QOS)。公式的问题是一个混合企业非线性程序(MINLP),通常是nphard。为了克服这个问题,我们将原始问题重构为双层优化问题,可以将其分解为两个子问题,以独立解决。外部问题是一个线性分配问题,可以通过著名的匈牙利方法有效地处理。内部问题仍然是一个非凸优化问题,为此找到最佳解决方案是具有挑战性的。但是,我们在封闭形式表达式中得出了HD和FD方案的最佳功率控制策略,这使得内部问题的计算复杂性是每种可能的配对配置的多项式。这些发现最终及时解决了原始的MILNP,使其适用于实时和低延迟应用。我们的仿真结果表明,所提出的框架在文献中的表现优于各种提出的方案,并且可以在可忽略不计的计算时间内获得与100个用户的网络的最佳配对和功率控制策略。
This paper investigates the performance of cooperative non-orthogonal multiple access (C-NOMA) in a cellular downlink system. The system model consists of a base station (BS) serving multiple users, where users with good channel quality can assist the transmissions between the BS and users with poor channel quality through either half-duplex (HD) or full-duplex (FD) device-to-device (D2D) communications. We formulate and solve a novel optimization problem that jointly determines the optimal D2D user pairing and the optimal power control scheme, where the objective is maximizing the achievable sum rate of the whole system while guaranteeing a certain quality of service (QoS) for all users. The formulated problem is a mixed-integer non-linear program (MINLP) which is generally NPhard. To overcome this issue, we reconstruct the original problem into a bi-level optimization problem that can be decomposed into two sub-problems to be solved independently. The outer problem is a linear assignment problem which can be efficiently handled by the well-known Hungarian method. The inner problem is still a non-convex optimization problem for which finding the optimal solution is challenging. However, we derive the optimal power control policies for both the HD and the FD schemes in closedform expressions, which makes the computational complexity of the inner problems polynomial for every possible pairing configurations. These findings solve ultimately the original MILNP in a timely manner that makes it suitable for real-time and low latency applications. Our simulation results show that the proposed framework outperforms a variety of proposed schemes in the literature and that it can obtain the optimal pairing and power control policies for a network with 100 users in a negligible computational time.