| The fifth generation wireless communication networks are expected to realize 1000-fold network capacity improvement.Network densification by densely deploying a set of low-power single-cell sites within the coverage of macrocell is identified as the most promising means to meet the requirement which significantly improves spatial multiplexing,extends the coverage and enhances the quality of service of users.Unlike previous mobile communication networks,the more internet of things devices will access the fifth generation mobile communication networks.Nevertheless,unpredictable and overwhelming inter-cell interference constitutes a new challenge because of the densely and highly disorganized network infrastructures.Therefore,mitigating inter-cell interference and improving energy efficiency while ensuring the quality of service of users have become the key issues.Consequently,radio resource management technology of ultra-dense networks has become the focus of the researchers.Interference management and resource allocation are mainly concerned in this paper which have a great impact on the performance of ultra-dense networks.The content of this paper is as follows: game theory and uplink power control,optimal fractional frequency reuse in LTE-A networks,cross-tier cooperation load-adapting interference management and optimal resource allocation for two-user and single-DF-relay network with ambient backscatter.Game theory is not only a new branch of modern mathematics,but also an important discipline of operational research.Since some of its basic assumptions match the expected goal of radio resource allocation very well,game theory has important value for researching resource allocation technology in ultra-dense networks.In theory,applying game theory to optimize radio resource allocation can achieve the optimal results.The disadvantage is that its computation is complex,but with the development of cloud computing,these problems will be solved gradually.This paper studies the application of game theory in uplink power control of ultra-dense networks.And combining the game theory and the uplink power control algorithm of heterogeneous network,a new uplink power control algorithm based on the game theory in heterogeneous network is proposed in this paper.The new algorithm applies the price payment function of game theory to the uplink power and power allocation algorithm.In heterogeneous network,any user’s power change should consider the generating interference to the other co-frequency users located in the network and use it as a price-based payment function to control the user uplink power.After multiple iterations,the optimal users’ uplink power can be obtained which results in the improvement of network performance.Fractional frequency reuse technology is a kind of easy to implement with the high reliability to mitigate inter-cell interference,which is widely deployed in realistic mobile communication networks.By studying this technology,we have analyzed its potential shortcomings while applied in ultra dense network.Then the fractional frequency reuse technology has been optimized while used in ultra dense network.Having been widely studied,a quasi-perfect resource allocation scheme for optimizing the performance of cell-edge users in fractional frequency reuse aided LTE-A multi-cell networks is proposed.Firstly,it splits cell-edge region and cell-center region,cell-edge bandwidth and cell-center bandwidth,cell-edge users and cell-center users into six parts and defines a different resource allocation priority for users in different zone.Secondly,each sector determines which zone the user should be located in based on its coordinates.Finally,each sector allocates the bandwidth to its serving users according to the predefined resource allocation priority.Therefore,the better performance for inter-cell interference coordination is achieved which results from the more uniform distance distribution among the users allocated the same bandwidth in different cells.Cross-tier cooperation is an effective method for resource management in ultra-dense networks.The existing wireless resource management algorithms of cross-tier cooperation in ultra-dense network are optimized based on the scenario that each cell’s traffic is fully loaded.However,in the realistic network,the payload changes with the time and cells.To tackle the densely deployed base stations and the cell traffic fluctuating with time,a cross-tier cooperation load-adapting interference management scheme in ultra-dense networks is proposed,which employs three technologies to mitigate inter-cell interference efficiently.Firstly,fractional frequency reuse technology is employed to coordinate the inter-cell interference among macro base stations as well as the inter-cell interference between macro base stations and small base stations.Secondly,we use load-adapting resource allocation technology to mitigate inter-cell interference further when the small base stations traffic is partially loaded.Thirdly,the interference-aware resource allocation can mitigate inter-cell interference further by optimizing the physical resource blocks mapping methods,which alleviates inter-cell interference by coordinating resource allocation for the users with higher transmit power among their neighboring base stations.Finally,resource allocation algorithm of the system where some nodes are based on ambient backscatter communication technology is studied in ultra-dense networks.Different from the existing schemes,a two-user single decode-and-forward relay network with ambient backscatter is analyzed and investigated,where the user nodes and relay node are equipped with a wireless powered device without embedded power supply.The decode-and-forward relay and the user close to receiver are integrated into one device to reduce deployment cost.A multi-step iterative optimization scheme is proposed for maximizing the system throughput in this paper.To solve this non-convex problem,the original problem is first divided into two non-convex sub-problems.By converting them into the convex problems,their optimal solutions are obtained by convex optimization method.Finally,the iterative algorithm is employed to achieve the maximum throughput of original problem by further optimizing the solutions of two sub-problem.Moreover,our proposed scheme also provides some useful insights to optimize multi-user multiple decode-and-forward relay multi-hop backscatter communication networks by dividing a complex optimization problem into several simple sub-optimization problems. |
