Game based robust power allocation strategy with QoS guarantee in D2D communication network
Introduction
Due to the scarcity of wireless spectrum resources, the requirements of large bandwidth and low delay in multimedia data transmission have brought great challenges to existing wireless communication systems [1], [2]. It is predicted that global mobile data traffic will increase at a compound annual growth rate of 47% by 2021 [2]. Accordingly, in order to improve the spectrum efficiency of cellular network and the communication quality of edge users, higher requirements are put forward for the next generation of mobile network architecture and key technologies [3]. Device to device multicast (D2MD) communication has great potential in improving spectrum utilization, reducing transmission delay, expanding coverage and reducing system energy consumption [4], [5], [6], [7].
There are many key technologies for D2MD communication. Firstly, it is about connection establishment and release of D2D multicast communication. In the connection establishment process of D2D multicast communication, the number of users increases, and the process of terminal discovery and synchronization is more complex. When these processes are completed by the base station, it will undoubtedly bring great pressure to the BS. Therefore, the CH can employ cognitive radio technology to monitor the communication range to reduce the burden of BS. Secondly, the radio resource allocation of D2D multicast communication is a key technology. For example, the power control algorithm of D2D multicast can flexibly adjust the required power to reduce the energy assumption. At the same time, power control is also an important way of interference management for D2D multicast communication. Thirdly, D2MD cluster head selection is also a key issue. In the D2MD scenario, in order to better serve the cell edge users that cannot be reached by the BS, the BS needs to select the CH as the relay in the multicast user group that can be served for D2D multicast communication. When selecting the cluster head, the base station should not only consider the coverage of the edge users, but also update the cluster head periodically for the frequently changing inter cluster channel conditions.
In this paper, we investigate a game theory-based robust power allocation strategy with QoS guarantee in D2D communication uplink network base on orthogonal frequency division multiplexing (OFDM). The Stackelberg game framework is introduced to model and analyze actions between the leaders (BS) and followers (D2D users) and the channel uncertainty is also taken into consideration. In the system, we consider that the users are grouped into different disjoint clusters. CUEs have authorized spectrum resources and D2D multiplexes the spectrum resources of CUEs in the same cluster, which causes great interference to the BS. Accordingly, for the BS, it aims to maximize its profit charging from D2D users, subjecting to a constraint of maximum tolerable interference. And for the DUEs, they attempt to maximize their profit in the network system while guaranteeing the QoS requirements for DUEs. Then, a distributed algorithm is developed to obtain the optimal transmission power of each cluster head (CH), which significantly reduces the information exchanges.
The rest of the paper is organized as follows. Section 2 will succinctly summarize the related work. In Section 3, we present the system model and give the optimization problem description. Then, in Section 4, the optimal resource allocation algorithm is studied. In Section 5, the simulation results are given to show the effectiveness of the proposed algorithm. Finally, conclusions are drawn in Section 6.
Section snippets
Related work
Because of the advantages in aspect of high transmitting rate, low latency, low power consumption, D2MD communication has attracted more and more attention in recent years [8], [9]. Meshgi et al. [10] formulated the general problem of power and channel allocation as a mixed integer nonlinear programming (MINLP) problem to maximize the sum throughput of CUES and feasible D2D multicast groups in a cell. Alwan et al. [11] proposed a novel scheme named Joint Multicast Routing and Wireless
System model and problem formulation
A single-cell D2D communication network is considered, where regular CUEs are distributed in the cell with radius . D2D users are clustered according to the farthest broadcast principle and distributed in the cluster with radius . We also assume that the total bandwidth is equally divided. In order to improve the user experience of edge users, D2D receivers (D2DR) and CH users are located at the junction of edge area and central area respectively. And CH users will multicast the data
Robust optimization distributed algorithm
The solution to the proposed non-cooperative game is derived in detail. Furthermore, in order to solve this problem, a robust optimization of distributed algorithm is proposed to deal with the game problem.
Simulation results and performance analysis
In this section, several simulation results are conducted for evaluating the performance of the proposed power control scheme in the D2D multicast network. It is set that there are six clusters. In a certain time slot, according to the assumption of TDMA communication mode, only one pair of D2D users communicate in each cluster. The convergence of the proposed Stackelberg game is tested and we validate the analytical expressions through Monte Carlo simulations. The major system parameters are
Conclusion
In this paper, we have investigated a game-based robust uplink power allocation strategy with QoS guarantee in D2D communication network. It has analyzed the behavioral strategy between the BS and D2D users by using dynamic game theory. For the BS, the interference observed at BS has been ensured below the maximum tolerable interference. For D2D users, a distributed power control algorithm has been presented to guarantee the QoS. Considering uncertain channel gains, probabilistic constraints
CRediT authorship contribution statement
Zhixin Liu: Conceptualization, Methodology, Supervision. Xiaopin Li: Methodology, Writing - original draft, Data curation. Yazhou Yuan: Investigation, Visualization. Yi Yang: Investigation, Writing - review & editing. Xinping Guan: Supervision, Writing - review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This work is partly supported by National Natural Science Foundation of China under grant 61873223, the Natural Science Foundation of Hebei Province, China under grant F2019203095, and the National Key R&D Program of China under grant 2018YFB1702100.
Zhixin Liu received his B.S., M.S., and Ph.D. degrees in control theory and engineering from Yanshan University, Qinhuangdao, China, in 2000, 2003, and 2006, respectively. He is currently a professor with the Department of Automation, School of Electrical Engineering, Yanshan University, China. He visited the University of Alberta, Edmonton, AB, Canada, in 2009. He is the author or a coauthor of more than 80 papers in technical journals and conference proceedings. His current research interests
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Zhixin Liu received his B.S., M.S., and Ph.D. degrees in control theory and engineering from Yanshan University, Qinhuangdao, China, in 2000, 2003, and 2006, respectively. He is currently a professor with the Department of Automation, School of Electrical Engineering, Yanshan University, China. He visited the University of Alberta, Edmonton, AB, Canada, in 2009. He is the author or a coauthor of more than 80 papers in technical journals and conference proceedings. His current research interests include performance optimization and energy-efficient protocol design in wireless sensor networks, wireless resource allocation in cognitive radio networks and Femtocell networks.
Xiaopin Li is currently working toward the M.S. degree in the School of Electrical Engineering, Yanshan University, China. His current research interests include wireless resources allocation, performance optimization of D2D networks.
Yazhou Yuan received his B.S., M.S. degrees in control science and engineering from Yanshan University, Qinhuangdao, China, in 2009, 2012, and Ph.D degree in Control Theory and Engineering from Shanghai Jiao Tong University in 2016. He is now an associate professor in the School of Electrical Engineering, Yanshan University, China. His research interests include resources allocation in wireless networks, industrial internet of things.
Yi Yang received her B.S., M.S. degrees in management science and engineering from Yanshan University, Qinhuangdao, China, in 2006, 2009, respectively. She is now an assistant researcher with the School of Electrical Engineering, Yanshan University, China. Her research interests include optimization theory and applications.
Xinping Guan received his B.S. degree in mathematics from Harbin Normal University, Harbin, China, in 1986 and his M.S. degree in applied mathematics and his Ph.D. degree in electrical engineering from the Harbin Institute of Technology in 1991, and 1999, respectively. He is currently a professor with the Department of Automation, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China. His current research interests include wireless sensor networks, congestion control of networks, robust control and intelligent control for nonlinear systems. Prof. Guan received a Special Appointment Professorship under the CheungKong Scholars Program by the Ministry of Education of China in 2005 and the National Science Fund for Distinguished Young Scholars of China in 2005. He became a Fellow of IEEE in 2018.