In this article,we use Intelligent Reflecting Surfaces(IRS)to improve the throughput of Non Orthogonal Multiple Access(NOMA)with Adaptive Transmit Power(ATP).The results are valid for Cognitive Radio Networks(CRN)wher...In this article,we use Intelligent Reflecting Surfaces(IRS)to improve the throughput of Non Orthogonal Multiple Access(NOMA)with Adaptive Transmit Power(ATP).The results are valid for Cognitive Radio Networks(CRN)where secondary source adapts its power to generate low interference at primary receiver.In all previous studies,IRS were implemented with fixed transmit power and previous results are not valid when the power of the secondary source is adaptive.In CRN,secondary nodes are allowed to transmit over the same band as primary users since they adapt their power to minimize the generated interference.Each NOMA user has a subset of dedicated reflectors.At any NOMA user,all IRS reflections have the same phase.CRN-NOMA using IRS offers 7,13,20 dB gain vs.CRN-NOMAwithout IRS for N=8,16,32 reflectors.We also evaluate the effects of primary interference.The results are valid for any number of NOMA users,Quadrature Amplitude Modulation(QAM)and Rayleigh channels.展开更多
A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifet...A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifetime.It takes the path loss exponent and the energy control coefficient into consideration with the aim to accentuate the minimum covering district of each node more accurately and precisely according to various network application scenarios.Besides,a self-healing scheme that enhances the robustness of the network was provided.It makes the topology tolerate more dead nodes than existing algorithms.Simulation was done under OMNeT++ platform and the results show that the LA-TPA strategy is more effective in constructing a well-performance network topology based on various application scenarios and can prolong the network lifetime significantly.展开更多
Data transmission through a wireless network has faced various signal problems in the past decades.The orthogonal frequency division multiplexing(OFDM)technique is widely accepted in multiple data transfer patterns at...Data transmission through a wireless network has faced various signal problems in the past decades.The orthogonal frequency division multiplexing(OFDM)technique is widely accepted in multiple data transfer patterns at various frequency bands.A recent wireless communication network uses OFDM in longterm evolution(LTE)and 5G,among others.The main problem faced by 5G wireless OFDM is distortion of transmission signals in the network.This transmission loss is called peak-to-average power ratio(PAPR).This wireless signal distortion can be reduced using various techniques.This study uses machine learning-based algorithm to solve the problem of PAPR in 5G wireless communication.Partial transmit sequence(PTS)helps in the fast transfer of data in wireless LTE.PTS is merged with deep belief neural network(DBNet)for the efficient processing of signals in wireless 5G networks.Result indicates that the proposed system outperforms other existing techniques.Therefore,PAPR reduction in OFDM by DBNet is optimized with the help of an evolutionary algorithm called particle swarm optimization.Hence,the specified design supports in improving the proposed PAPR reduction architecture.展开更多
To obtain good trade-offs between complexity and performance onpeak-to-average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM)using partial transmitting sequence (PTS) schemes, a trel...To obtain good trade-offs between complexity and performance onpeak-to-average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM)using partial transmitting sequence (PTS) schemes, a trellis structure based PTS factor searchmethod is proposed. The trellis search is with a variant constraint length L_C, 1 ≤ L_C ≤ V-1,where V is the number of PTS subblocks. The method is to decide a PTS factor by searching all thepossible paths obtained by varying L_C consecutive factors. The trellis search can be viewed as ageneral PTS factor search model. If L_C = V-1, it is a full search, and if L_C = 1, it is aniterative search. Using different constraint lengths, trellis factor search PTS exhibits differentPAPR reduction performances. A larger L_C results in a better performance and L_C = V-1 results inthe optimum. However, a larger L_C requires more computation. This helps to choose a good trade-offbetween complexity and performance.展开更多
因移动便捷、高视距通信概率等优势,无人机(Unmanned Aerial Vehicle,UAV)在应急通信中发挥重要作用。为此,提出联合优化UAVs位置和传输功率的吞吐量最大化(Joint optimization of UAV 3-D Position and Transmit powers for throughput...因移动便捷、高视距通信概率等优势,无人机(Unmanned Aerial Vehicle,UAV)在应急通信中发挥重要作用。为此,提出联合优化UAVs位置和传输功率的吞吐量最大化(Joint optimization of UAV 3-D Position and Transmit powers for throughput Maximization,JPTM)方法,进而提高地面用户的吞吐量。先构建一个联合UAVs三维位置和传输功率的优化问题。考虑到该问题的非凸优化性,将其分解为两个子问题。用Mean-Shift算法求解第一个问题,获取最优的UAVs水平位置。采用分而治之策略,将第二个子问题再分解,并利用一阶泰勒级数展开对两个子问题进行近似处理,形成标准凸化问题,然后利用CVX工具求解。性能分析表明,相比于基于圆形堆积理论部署UAVs策略(Circle Packing Theorem-based Deployment,CPTD)和基于多变量仿真的能效UAVs部署策略(Energy-Efficient Variable simultaneous Deployment,EEVD)算法,JPTM算法提高了地面用户的吞吐量。展开更多
基金The authors extend their appreciation to the Deanship of Scientific Research at Saudi Electronic University for funding this research work through the Project Number 8093.
文摘In this article,we use Intelligent Reflecting Surfaces(IRS)to improve the throughput of Non Orthogonal Multiple Access(NOMA)with Adaptive Transmit Power(ATP).The results are valid for Cognitive Radio Networks(CRN)where secondary source adapts its power to generate low interference at primary receiver.In all previous studies,IRS were implemented with fixed transmit power and previous results are not valid when the power of the secondary source is adaptive.In CRN,secondary nodes are allowed to transmit over the same band as primary users since they adapt their power to minimize the generated interference.Each NOMA user has a subset of dedicated reflectors.At any NOMA user,all IRS reflections have the same phase.CRN-NOMA using IRS offers 7,13,20 dB gain vs.CRN-NOMAwithout IRS for N=8,16,32 reflectors.We also evaluate the effects of primary interference.The results are valid for any number of NOMA users,Quadrature Amplitude Modulation(QAM)and Rayleigh channels.
基金Projects(61101104,61100213) supported by the National Natural Science Foundation of ChinaProject(NY211050) supported by Fund of Nanjing University of Posts and Telecommunications,China
文摘A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifetime.It takes the path loss exponent and the energy control coefficient into consideration with the aim to accentuate the minimum covering district of each node more accurately and precisely according to various network application scenarios.Besides,a self-healing scheme that enhances the robustness of the network was provided.It makes the topology tolerate more dead nodes than existing algorithms.Simulation was done under OMNeT++ platform and the results show that the LA-TPA strategy is more effective in constructing a well-performance network topology based on various application scenarios and can prolong the network lifetime significantly.
文摘Data transmission through a wireless network has faced various signal problems in the past decades.The orthogonal frequency division multiplexing(OFDM)technique is widely accepted in multiple data transfer patterns at various frequency bands.A recent wireless communication network uses OFDM in longterm evolution(LTE)and 5G,among others.The main problem faced by 5G wireless OFDM is distortion of transmission signals in the network.This transmission loss is called peak-to-average power ratio(PAPR).This wireless signal distortion can be reduced using various techniques.This study uses machine learning-based algorithm to solve the problem of PAPR in 5G wireless communication.Partial transmit sequence(PTS)helps in the fast transfer of data in wireless LTE.PTS is merged with deep belief neural network(DBNet)for the efficient processing of signals in wireless 5G networks.Result indicates that the proposed system outperforms other existing techniques.Therefore,PAPR reduction in OFDM by DBNet is optimized with the help of an evolutionary algorithm called particle swarm optimization.Hence,the specified design supports in improving the proposed PAPR reduction architecture.
文摘To obtain good trade-offs between complexity and performance onpeak-to-average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM)using partial transmitting sequence (PTS) schemes, a trellis structure based PTS factor searchmethod is proposed. The trellis search is with a variant constraint length L_C, 1 ≤ L_C ≤ V-1,where V is the number of PTS subblocks. The method is to decide a PTS factor by searching all thepossible paths obtained by varying L_C consecutive factors. The trellis search can be viewed as ageneral PTS factor search model. If L_C = V-1, it is a full search, and if L_C = 1, it is aniterative search. Using different constraint lengths, trellis factor search PTS exhibits differentPAPR reduction performances. A larger L_C results in a better performance and L_C = V-1 results inthe optimum. However, a larger L_C requires more computation. This helps to choose a good trade-offbetween complexity and performance.
文摘因移动便捷、高视距通信概率等优势,无人机(Unmanned Aerial Vehicle,UAV)在应急通信中发挥重要作用。为此,提出联合优化UAVs位置和传输功率的吞吐量最大化(Joint optimization of UAV 3-D Position and Transmit powers for throughput Maximization,JPTM)方法,进而提高地面用户的吞吐量。先构建一个联合UAVs三维位置和传输功率的优化问题。考虑到该问题的非凸优化性,将其分解为两个子问题。用Mean-Shift算法求解第一个问题,获取最优的UAVs水平位置。采用分而治之策略,将第二个子问题再分解,并利用一阶泰勒级数展开对两个子问题进行近似处理,形成标准凸化问题,然后利用CVX工具求解。性能分析表明,相比于基于圆形堆积理论部署UAVs策略(Circle Packing Theorem-based Deployment,CPTD)和基于多变量仿真的能效UAVs部署策略(Energy-Efficient Variable simultaneous Deployment,EEVD)算法,JPTM算法提高了地面用户的吞吐量。
