M2M energy saving strategy in 5G millimeter wave system

Abstract

M2M (Machine to Machine) technology has a broad application prospect in 5G network, but one of the bottlenecks is the energy consumption of intelligent devices powered by battery. In this paper, we study the energy saving strategy in 5G millimeter wave system. Firstly, a Discontinuous Reception scheme based on Beam Measurement (BM-DRX) is proposed to avoid the unnecessary beamforming. Secondly, by modifying the frame structure and optimizing the beamforming, the time of beamforming is further shortened and the power consumption is also saved. Finally, based on the ETSI (European Telecommunications Standards Institute) data model, the beam misalignment events are regarded as Poisson distribution, and the semi-Markov process is used to analyze the BM-DRX. Simulation results show that the proposed scheme can not only meets the delay performance, but also saves the energy consumption of the system. INDEX TERMS 5G, M2M, BM-DRX, energy saving, delay I. INTRODUCTIONIn the Fifth Generation (5G) communication networks, some strategies are used to satisfy the demands of growing data capacity, data rate and provide the best quality of service requirements. Firstly, in order to improve the data bandwidth and connection efficiency, achieve better download and upload speed and less delay, bands are specified in two Frequency Ranges (FR) in 3GPP Release 15. FR1 ranges from 450 MHz to 6000 MHz, known as cmWave. FR2 ranges from 24250 MHz to 52600 MHz, which are commonly referred to as mmWave. Moreover, some technology such as beamforming are use in 5G network. References [1], [2] show that millimeter wave spectrum can support high-speed data rate by using beamforming technology with multi-antenna arrays. Efficient beamforming is helpful to improve spectrum efficiency, reduce system interference and enhance wireless communication security. At the same time, with the rapid development of electronics and computer, the intelligent devices can fulfill the requirement of higher bandwidth service [3]. M2M (Machine to Machine) communication is widely used in 5G Internet of Things (IoT) [4], including the fields of industrial vehicle network, automation, smart grid, telemedicine, etc. With the exponential growth of the number of M2M intelligent devices, the data flow is expanding rapidly. The increasing of M2M devices will not only affect Access Networks (ANs) but also Core Networks (CNs). Because most of the devices are powered by battery, such as intelligent wearable devices, UAVs (unmanned aerial vehicles), intelligent electric meters, the power saving of intelligent device is a crucial issue for the 5G M2M network. Thus, increasing energy efficiency in mobile networks will reduce the costs of capital and operational expenditures. It makes energy efficiency extremely important. There are many energy saving technologies for 5G wireless networks. Some recent researches on green 5G technology and communication energy harvest are reviewed in reference [5]. Some new technologies are also discussed related to energy saving technology includi...

Power efficient stochastic modeling for Narrowband Internet of Things devices in 5G networks

“…For the beam measurement and beamforming, a threshold level is set to make certain beam pairing between UE and base station rather than full beamforming. 26 The higher level of beam pair than the threshold makes the UE sends feedback and make a channel with the base station to receive packets else beamforming is required till the threshold value instead of full beamforming. For the 5G base station having P beams to sweep at any instant and UE having Q beams to sweep at any instant, the average time considered for the beam search is P * Q * L∕4, where L is the frame length which consists of a fixed number of time slots.…”

“…For the 5G base station having P beams to sweep at any instant and UE having Q beams to sweep at any instant, the average time considered for the beam search is P * Q * L∕4, where L is the frame length which consists of a fixed number of time slots. 26 Further, with the employment of the two-stage method, steady-state probabilities for the SMM are calculated.…”

“…A deep survey of physical layer technologies and beamforming algorithms for 5G wireless networks was provided by Agiwal et al 24 Huang et al 25 proposed the model of the static and dynamic serving beam patterns for the DRX mechanism employed in the 5G networks and beyond. Shen et al 26 proposed a beam measurement‐based DRX mechanism for Machine‐to‐Machine (M2M) devices in RRC connected mode. They settled a minimum level threshold to ensure the beam pairing among the base station and UE.…”

“…In order to meet the above mentioned challenges, this work proposes SMM with beam measurement and beamforming‐based DRX mechanism in RRC modes. For the beam measurement and beamforming, a threshold level is set to make certain beam pairing between UE and base station rather than full beamforming 26 . The higher level of beam pair than the threshold makes the UE sends feedback and make a channel with the base station to receive packets else beamforming is required till the threshold value instead of full beamforming.…”

“…The higher level of beam pair than the threshold makes the UE sends feedback and make a channel with the base station to receive packets else beamforming is required till the threshold value instead of full beamforming. For the 5G base station having $$$ P $$$ beams to sweep at any instant and UE having $$$ Q $$$ beams to sweep at any instant, the average time considered for the beam search is $$$ P\ast Q\ast L/4 $$$, where $$$ L $$$ is the frame length which consists of a fixed number of time slots 26 . Further, with the employment of the two‐stage method, steady‐state probabilities for the SMM are calculated.…”