College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China.
State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an 710071, China.
Sensors (Basel). 2018 Aug 3;18(8):2542. doi: 10.3390/s18082542.
Accommodating massive connectivity for Internet of Things (IoT) applications is considered an important goal of future 5G cellular systems. Nonorthogonal multiple access (NOMA), which enables a group of mobile users to simultaneously share the same spectrum channel for transmission, provides an efficient approach to achieve the goals of spectrum-efficient data delivery. In this paper, we consider an uplink transmission in a sensor network in which a group of smart terminals (e.g., sensors) use NOMA to send their collected data to an access point. We aim to minimize the total radio resource consumption cost, including the cost for the channel usage and the cost for all senors' energy consumption to allow the sensors to complete their data delivery requirements. Specifically, we formulate a joint optimization of the decoding-order, transmit-power and time allocations to study this problem and propose an efficient algorithm to find the optimal solution. Numerical results are provided to validate our proposed algorithm and the performance advantage of our proposed joint optimization for the uplink data collection via NOMA transmission.
为物联网 (IoT) 应用提供大容量连接被认为是未来 5G 蜂窝系统的重要目标。非正交多址接入 (NOMA) 技术允许一组移动用户同时共享相同的频谱信道进行传输,为实现高效的数据传输提供了一种有效的方法。在本文中,我们考虑了传感器网络中的上行链路传输,其中一组智能终端(例如传感器)使用 NOMA 将其收集的数据发送到接入点。我们的目标是最小化总无线电资源消耗成本,包括信道使用成本和所有传感器的能耗成本,以使传感器能够完成其数据传输要求。具体来说,我们联合优化解码顺序、发射功率和时间分配,以研究这个问题,并提出了一种有效的算法来找到最优解。数值结果验证了所提出算法的有效性以及通过 NOMA 传输进行上行数据收集的联合优化的性能优势。