M2M communication is an important component for future wireless networks. M2M systems consist of a large number of devices that can operate with minimum or no human intervention. However, spectrum demand rises exponentially with the increase in the number of connected devices. Cognitive 5G networks are key to address the issue of spectrum scarcity. Further, use of multiple gateways in cognitive 5G networks for M2M communication can increase system throughput, coverage, and energy efficiency. Nevertheless, using multiple gateways for the secondary M2M devices may cause interference to the primary M2M devices. Existing gateway selection protocols for cognitive M2M communication mostly use single channel CSMA, and thus are not efficient in terms of reducing the interference. Thus, in this article, we propose a DGAP based on multi-channel CSMA for M2M communication in 5G networks. Further, we propose a Lo-DGAP, where each gateway transmits only the worst primary M2M device information rather than transmitting all neighboring primary M2M device information. The proposed Lo-DGAP increases the throughput of the system by reducing the message header payload and is also energy- efficient. Simulation results demonstrate the effectiveness of the proposed schemes in terms of network lifetime and energy consumption.

中文翻译：

---

认知5G网络中用于M2M通信的分布式网关选择

M2M通信是未来无线网络的重要组成部分。M2M系统由大量设备组成，这些设备可以在最少或没有人为干预的情况下运行。但是，频谱需求随着连接设备数量的增加而呈指数增长。认知5G网络是解决频谱稀缺问题的关键。此外，在认知5G网络中使用多个网关进行M2M通信可以提高系统吞吐量，覆盖范围和能源效率。但是，将多个网关用于辅助M2M设备可能会对主M2M设备造成干扰。现有的用于认知M2M通信的网关选择协议大多使用单信道CSMA，因此在减少干扰方面效率不高。因此，在本文中，我们提出了一种基于多通道CSMA的DGAP，用于5G网络中的M2M通信。此外，我们提出了Lo-DGAP，其中每个网关仅发送最差的主要M2M设备信息，而不发送所有相邻的主要M2M设备信息。所提出的Lo-DGAP通过减少消息头的有效载荷来增加系统的吞吐量，并且也是节能的。仿真结果证明了所提方案在网络寿命和能耗方面的有效性。