Research On Wireless Resource Optimization Mechanism Based On Non-orthogonal Multiple Access

With the rapid development of mobile communication industry,mobile communication technology is faced with many challenges,like the increasing number of devices,higher requirements for spectral efficiency and computation capability.In order to meet these challenges,many communication technologies have emerged,among which non-orthogonal multiple access(NOMA)is a promising technology.Unlike traditional orthogonal multiple access(OMA),NOMA allows multiple users to share the same time/frequency resource block and use different power levels to differentiate the signals of different users.The receiver then applies successive interference cancellation(SIC)for multiuser detection and decoding.Benefitting from power domain multiplexing,NOMA can significantly improve the number of users and spectrum efficiency in mobile communication systems.However,NOMA also bears the difficulty of the wireless resource management that power domain multiplexing brings.Wireless resource in NOMA system mainly includes power and time-frequency resource.Considering that different users have different quality of service(QoS)requirements,how to reduce inter-user interference through power allocation with QoS constraints is very important;The allocation of timefrequency resources in the NOMA system is also called user grouping.Different grouping strategies mean that different power allocation schemes are needed to eliminate interference.Therefore,user grouping and power allocation are closely coupled together,and the joint optimization of user grouping and power allocation is needed to improve NOMA performance.In multi-cell scenarios,edge users do not only suffer intra-group interference but also inter-cell interference,which makes the joint optimization of user grouping and power allocation more complicated.In addition,with the popularity of emerging applications such as virtual reality and augmented reality,higher computation capability is required by mobile devices to deal with the growing computation demands of data processing tasks,especially video processing tasks.Therefore,many researchers consider constructing an integrated network of communication and computing by deploying mobile edge computing(MEC)servers with base stations(BSs)and offloading part of mobile devices’ data processing tasks to MEC servers by NOMA.However,the amount of computing tasks that need to be offloaded is very large,which brings great challenges to NOMA transmission.To cope with these challenges,this dissertation mainly studied the following contents:1)For the wireless resource management of downlink NOMA systems,this dissertation proposes a joint optimization strategy for user grouping and power allocation.Recently,many works have studied the user grouping strategies based on channel conditions in NOMA systems.However,in fact,the diverse QoS requirements of users will also affect the effect of user grouping.In addition,in NOMA downlink multi-cell scenarios,inter-cell interference will increase the difficulty of power allocation,and how to choose the optimal user grouping strategy considering inter-cell interference and diverse QoS requirements is still an open problem.This dissertation studies the QoS-aware user grouping strategy with the aim of minimizing the total transmit power in downlink multi-cell NOMA systems.The problem of user grouping in downlink multi-cell NOMA systems is established as a game model,where each BS is a player.This dissertation characterizes inter-cell interference by the interaction among the players in this game,and proves that in this game,the problem of finding a user grouping strategy for each player can be transformed into the problem of finding a specific negative loop in a graph composed of users.Bellman-Ford algorithm is extended to find these negative loops.Furthermore,this dissertation designs a greedy-based suboptimal strategy that approximates the optimal solution in polynomial time.Extensive simulations validate the effectiveness of grouping users considering QoS requirements and inter-cell interference and show that the proposed strategies can significantly reduce total transmit power consumption compared to the reference strategies.2)For the wireless resource management of uplink NOMA systems,this dissertation proposes a joint optimization strategy of user association,grouping,and power allocation in NOMA uplink transmission scenarios.Considering that the transmit power of each user is limited,reducing the total transmit power becomes more urgent and challenging.Due to the intra-group interference caused by power domain multiplexing,when allocating uplink transmit power,users should not only consider their own QoS requirements but also consider reducing interference to other users.In addition,in multi-cell scenarios,a user may prefer to associate with the BS with less interference rather than the nearest BS.Inter-user interference makes uplink wireless resource management more complex,so it is necessary to quantitatively analyze the interference that a user brings to the others in the same group(externality)and perform uplink NOMA wireless resource management accordingly.However,there is no user grouping work based on that interference in multi-cell uplink NOMA systems currently.To this end,this dissertation first deduces an externality function to describe the interference among users in uplink NOMA systems.Then,this dissertation obtains the exact potential game model of the joint user association,user grouping,and power allocation problem in uplink NOMA systems,where each user is a player.This dissertation proves the existence of Nash equilibrium(NE)of this game.A heuristic algorithm to find the NE of the game is proposed.Simulation results show that the algorithm can significantly reduce the total transmit power compared with the existing schemes.3)For the wireless resource management of NOMA-assisted integrated networks of communication and computing,this dissertation proposes a joint optimization strategy of wireless resources and computation resources in a NOMA-assisted edge offloading framework with multiple MEC servers.In NOMA-assisted integrated networks of communication and computing,the total delay of each computation task can be divided into two parts:the delay of NOMA-based uplink wireless transmission and the delay of processing computation task at the MEC server.In order to meet the delay requirements of mobile devices,the wireless resource management for uplink transmission based on NOMA and the computation resource management at MEC server are coupled with each other.Therefore,in order to improve the efficiency of edge offloading in NOMA-assisted integrated network of communication and computing,it is necessary to joint optimize the management of wireless and computation resources,which makes the design of resource management scheme more challenging.To address these challenges,this dissertation proposes a novel NOMA-assisted task offloading framework with multiple MEC servers,and jointly optimizes the mobile device association strategy,uplink data transmission assisted by NOMA,task division as well as computation resource allocation at MEC server to minimize the total latency of all device while satisfying the delay requirements for all mobile devices.Simulation results show that the joint optimization strategy in the NOMA-assisted multi MEC framework proposed in this dissertation can significantly improve the system performance.Considering the diverse QoS requirements of users,this dissertation studies the problem of wireless resource management in uplink and downlink multi-cell NOMA systems.In addition,this dissertation has also applied NOMA to integrated networks of communication and computing to reduce the total delay of computation offloading.This dissertation proposes some algorithms to solve those problems based on graph theory,game theory,and convex optimization.The superiority of the proposed algorithms is verified by simulation.The results from three research topics clearly demonstrate that NOMA-based techniques are capable of improving the performance of wireless communication systems as well as the user experiences.