Precoding Performance Analysis And Resource Allocation Scheme Design For Massive MIMO In Cognitive Radio Ad Hoc Networks

With the rapid development of wireless communications,the demand for multimedia data services is accelerating,which makes spectrum a scarce resource.Researches show that the main benefits of massive MIMO systems are: serving more terminals in the same time-frequency resources simultaneously,higher data rate and lower power consumption and so on.This paper combine massive MIMO with CRAHNs,then reap all their benefits to satisfy the high performance requirements of modern wireless communication networks.Based on this background,the thesis focuses on the system performance and resource allocation schemes based on Massive MIMO in CRAHNs network.First of all,we investigate the performance of linear precoding in Massive MIMO system.According to the simulation results of the system,it is proposed that in the multi node Massive MIMO scenario,the ergodic capacity of the system is decreased with the increase of the number of nodes in the system.According to the theory,a new algorithm is proposed to compute the optimal number of nodes in the system.The algorithm adopts a very efficient technigue of one dimensional search.At last,the algorithm is validated by simulation.The algorithm is proved to be accuracy and reliable.The research shows that it is necessary to give full play to the advantages of Massive MIMO technology through reasonable allocation of system resources.Secondly,this paper does some derivations about the lower capacity bounds of Massive MIMO downlink systems in CRAHNs network when they adopt MRT and ZF pre coding.This paper also conducts some simulation to prove it.According to the results,a procedure of precoding algorithm schemes selection is proposed which takes into account the maximum power of each node.This procedure chooses the better precoding no matter the amount of users change.Simulation results indicate that the proposed scheme can maximize the system sum capacity in a low computational complexity.Finally,in order to decrease the carbon emission by energy consumption of wireless communication networks,an algorithm is proposed for energy-efficient resource allocation scheme in massive MIMO communication system.A convex optimization issue is provided with the objective of maximizing system energy efficiency lower bound under the minimum required data rate,maximum required power of each user and tolerable interference level constraint,meanwhile the cluster head uses a maximum rate transmitting(MRT)precoding.First,an iterative algorithm derived from optimality condition for bandwidth assignment is proposed.Second,according to the properties of fractional programming,the resulting energy-efficient optimization in the fractional form is transformed into subtractive form.Convex optimization is exploited to obtain the numbers of antennas and optimal transmit power of each user which lead to maximum energy efficiency.Simulation results show that the proposed schemes not only have less iteration number but also have good perform for system energy efficiency and throughput,at the same time,the performance of spectral-efficiency of the proposed algorithm is very well and the complexity is significantly reduced.