Abstract
With the rapid growth of Internet-of-things (IoT) devices, IoT communication has become an increasingly crucial part of 5G wireless communication systems. The large-scale IoT devices access results in system overload and low utilization of energy efficiency under the existing network framework. In this paper, the cluster head uses the LTE-M protocol, and the intra-cluster uses the low-power wide-area network (LPWAN) self-networking protocol in the wireless sensor network. By a detailed analysis of the messages exchanged between the device and the base station, we describe the causes of overload and the steps of data aggregate combined with the physical channel. Then, we explore the cluster head quantity and the optimal scale in the intra-cluster under the traditional K-mean algorithm. When K is 30 under specific resources, the simulation results show that the system’s access success probability and resource utilization are optimal. Also, we propose a distributed dynamic cluster-head selection and clustering scheme based on an improved K-means algorithm. Simulation results show that the proposed scheme can reach 88.07% on the access success probability. The throughput and resource utilization are 3.5 times high than that of the optimal K-means.
Highlights
Massive machine type communication is one of the main scenes of 5G wireless communication.Cisco estimates that 70% of IoT device connections will serve by the 3rd Generation Partner Project (3GPP) developed networks [1] because the existing cellular network has broad coverage, a large amount of deployed infrastructure, a complete user service management system, and so on
We give the main reason for the collision and we propose a distributed dynamic cluster-head selection and clustering scheme based on an improved K-means algorithm
In order to reflect the effect of the improved k-means algorithm of the proposed adaptive clustering on the energy efficiency, we first built an access simulation platform based on Matlab
Summary
Massive machine type communication is one of the main scenes of 5G wireless communication. It is primarily to improve the random access process to alleviate the problem of high collision probability, thereby reducing waste and achieving energy efficiency optimization It mainly divides into two research ideas. We analyze the communication process combined with the channel resources including random access and data transmission under the existing network system structure developed by 3GPP. We use a noise-based density-based method to pre-separate clusters, obtain the required number of cluster heads and initial positions according to the distribution of devices in the region, and solve the actual process access problem of excessive energy consumption in the cluster head. We analyze the communication process combined with the channel resources including random simulation results show that the proposed algorithm can significantly improve the system energy access and data transmission under the existing network system structure developed by 3GPP. The system model considered in this paper definedand in solve the numerical actual process access problem of excessive energy consumption inconclusions
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