Multiuser Gain in Energy Harvesting Wireless Communications

In traditional wireless communications, multiuser diversity gain comes from the diversified channel power gains across different users. In energy harvesting wireless systems, the various energy levels at different transmitters may lead to another type of diversity gain. In this paper, <italic>multiuser gain</italic> with the emphasis on <italic>energy diversity</italic> is studied for multiuser energy harvesting communications, where the scaling law of the expected throughput over the number of users is investigated. Three access schemes are considered: two centralized schemes (fixed TDMA, where users transmit in a fixed order; and energy-greedy, where the user with the highest energy level is picked for transmission) and a contention-based distributed scheme (where each user contends for the channel with a certain probability). Under both centralized schemes, it is shown that the expected throughput scales on the order of <inline-formula> <tex-math notation="LaTeX">$\log (N)$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> is the number of users. For the distributed scheme, the scaling of throughput depends on the contention probability. Particularly, when each user contends the transmission with probability <inline-formula> <tex-math notation="LaTeX">$1/N$ </tex-math></inline-formula>, the throughput also scales on the order of <inline-formula> <tex-math notation="LaTeX">$\log (N)$ </tex-math></inline-formula> but with a discount factor <inline-formula> <tex-math notation="LaTeX">$1/e$ </tex-math></inline-formula>. Our analytical and numerical results reveal that compared with the point-to-point energy harvesting communication system, the multiuser throughput gain comes from two aspects: the power gain due to the increase of total energy arrivals; and the diversity gain due to the increase of energy arrival dynamics.

[1]  Kaibin Huang,et al.  Spatial Throughput of Mobile Ad Hoc Networks Powered by Energy Harvesting , 2011, IEEE Transactions on Information Theory.

[2]  Kaibin Huang,et al.  Energy Harvesting Wireless Communications: A Review of Recent Advances , 2015, IEEE Journal on Selected Areas in Communications.

[3]  B. D. Vries,et al.  Renewable energy sources: Their global potential for the first-half of the 21st century at a global level: An integrated approach , 2007 .

[4]  Shuguang Cui,et al.  A general utility optimization framework for energy-harvesting-based wireless communications , 2015, IEEE Communications Magazine.

[5]  S. Asmussen,et al.  Applied Probability and Queues , 1989 .

[6]  Shuguang Cui,et al.  Throughput Maximization for the Gaussian Relay Channel with Energy Harvesting Constraints , 2011, IEEE Journal on Selected Areas in Communications.

[7]  Xiaodong Wang,et al.  Optimal Energy-Bandwidth Allocation for Energy-Harvesting Networks in Multiuser Fading Channels , 2016, IEEE Journal on Selected Areas in Communications.

[8]  Vinod Sharma,et al.  Capacity of Gaussian Channels With Energy Harvesting and Processing Cost , 2014, IEEE Transactions on Information Theory.

[9]  Fuad E. Alsaadi,et al.  Performance Analysis for Energy Harvesting Communication Systems: From Throughput to Energy Diversity , 2014, 2015 IEEE Global Communications Conference (GLOBECOM).

[10]  Wan Choi,et al.  The Two-User Gaussian Interference Channel With Energy Harvesting Transmitters: Energy Cooperation and Achievable Rate Region , 2015, IEEE Transactions on Communications.

[11]  Jing Yang,et al.  Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies , 2011, IEEE Journal on Selected Areas in Communications.

[12]  Lizhong Zheng,et al.  Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels , 2003, IEEE Trans. Inf. Theory.

[13]  Cihan Tepedelenlioglu,et al.  Multi-User Diversity with Random Number of Users , 2011, IEEE Transactions on Wireless Communications.

[14]  Randall Berry,et al.  Distributed approaches for exploiting multiuser diversity in wireless networks , 2006, IEEE Transactions on Information Theory.

[15]  Hussein Zedan,et al.  A comprehensive survey on vehicular Ad Hoc network , 2014, J. Netw. Comput. Appl..

[16]  Shuguang Cui,et al.  Optimal Power Allocation for Outage Probability Minimization in Fading Channels with Energy Harvesting Constraints , 2012, IEEE Transactions on Wireless Communications.

[17]  Xiaodong Wang,et al.  Iterative Dynamic Water-Filling for Fading Multiple-Access Channels With Energy Harvesting , 2014, IEEE Journal on Selected Areas in Communications.

[18]  Rui Zhang,et al.  Optimal Energy Allocation for Wireless Communications With Energy Harvesting Constraints , 2011, IEEE Transactions on Signal Processing.

[19]  Vinod Sharma,et al.  Optimal energy management policies for energy harvesting sensor nodes , 2008, IEEE Transactions on Wireless Communications.

[20]  Fuad E. Alsaadi,et al.  Resource Allocation for Multiple Access Channel With Conferencing Links and Shared Renewable Energy Sources , 2015, IEEE Journal on Selected Areas in Communications.

[21]  Marimuthu Palaniswami,et al.  Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..

[22]  Wan Choi,et al.  Multi-user diversity in a spectrum sharing system , 2009, IEEE Transactions on Wireless Communications.

[23]  Ping Zhang,et al.  Distributed Opportunistic Scheduling for Energy Harvesting Based Wireless Networks: A Two-Stage Probing Approach , 2015, IEEE/ACM Transactions on Networking.

[24]  Jeffrey G. Andrews,et al.  What Will 5G Be? , 2014, IEEE Journal on Selected Areas in Communications.

[25]  Jeffrey G. Andrews,et al.  Fundamentals of Heterogeneous Cellular Networks with Energy Harvesting , 2013, IEEE Transactions on Wireless Communications.

[26]  Shuguang Cui,et al.  Centralized Approaches for Exploiting Multiuser Energy Diversity in Energy Harvesting Communications , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[27]  C. Klüppelberg,et al.  Modelling Extremal Events , 1997 .