Resource Management For SCMA Based Wireless Networks

With the increasing demand of high-speed data services and large-scale access of Internet Of Things(IOT)devices,the orthogonal frequency division multiple access(OFDMA)technology employed by the 4th generation mobile communications system(4G)has been unable to meet the needs of the future wireless communications system.The development of the new multiple access technologies is an important way to meet the requirements of the 5th generation mobile communications system(5G),such as high speed,low latency,high reliability and massive equipment connection.Currently,the sparse code multiple access(SCMA)technology is highly expected because it can carry more number of users and greater system capacity with traditional time-frequency resources through controlling the interference among users and the decoding complexity of the receivers,and has become one of the candidate air interface technology for the next generation wireless communication networks.In addition,in order to further enhance the spectral efficiency of the network,5G system will also use a variety of other spectrum multiplexing technologies,such as Deviceto-Device(D2D)communicaiton technology,ultra dense network technology,and so on,while employs the new multiple access technology.However,the combined use of spectrum multiplexing technologies makes the interference in the wireless network become more and more complex and serious,which brings severe challenges to the design of resource management algorithm.In view of the above discussion,we investigate the resource management algorithm for SCMA based wireless network.Firstly,the resource management and the optimization of energy efficiency techniques in SCMA based D2 D underlaying cellular networks are studied.Then,aiming at the trend of network intensive development,this paper studies the resource allocation technologies of low energy consumption in dense networks.Specifically,the main contents and contributions are summarized as follows.1.This paper has investigated the resource management problem for D2 D underlaying cellular network.In particular,cellular users employ SCMA while D2 D users employ OFDMA.Specifically,we formulate it as an optimization problem to minimize the total energy consumption of cellular users and D2 D users subject to quality-of-service requirements,codebook assignment and subcarrier reuse constraints.To tackle this problem efficiently,we first construct an interference graph to depict the cross-tier interference amoung cellular users and D2 D users,based on which an efficient resource allocation algorithm is devised to well coordinate the cross-tier interference.Then,we propose an easily implemented iterative power control scheme to optimize the transmit power of all users.Finally,we compared the proposed algorithm with two other classical algorithms in terms of the user total tranmmit power and interference of the wireless network.The simulation results exhibit that our algorithms can better coordinate the system interference and reduce the system power consumption.2.This paper has mainly studied the total transmission power of users minimization problem in SCMA based dense network.Due to its mixed combinatory,the global optimal solution usually requires high computational complexity.Therefore,we propose base station clustering,resource allocation and power control algorithm with low complexity.Specifically,we firstly designed a distributed base station clustering protocol under the assumption of equal user transmission power.Then,the problem of minimizing the total user transmit power of was transformed into the transmit power minimization problem of a single cluster through clustering the base stations,and then the multi-cell joint resource allocation algorithm was used to coordinate the inter cell interference in a base station cluster.Finally,under the premise of ensuring the quality of service(Qo S),we adopt an easily implemented iterative power control scheme to optimize the transmit power of all users.Extensive simulation results exhibit the performance gain of our algorithms as compared with other schemes.