Aiming at the problem of resource allocation in multiuser multi-input multi-output (MIMO)systems,a new power allocation algorithm based on dual waterfilling is proposed.Block diagonalization is adopted to cancel the i...Aiming at the problem of resource allocation in multiuser multi-input multi-output (MIMO)systems,a new power allocation algorithm based on dual waterfilling is proposed.Block diagonalization is adopted to cancel the inter-user interference,and then the complete diagonalization method is employed to derive the spatial sub-channels for each user.The overall power of the system is divided among users based on each user’s large scale fading;then the power of each user is further allocated to its spatial sub-channels based on the small scale fading.Simulation results show that compared with the existing resource allocation strategies,the proposed algorithm can provide more ergodic capacity for multi-user MIMO systems.When the total transmit power is 100w,it has 15%capacity advantage over the traditional waterfilling method.展开更多
Cognitive Radio(CR) is a promising technique for the next generation mobile communi-cation system for its capability to solve the conflicts between the scarcity and underutilization of spectrum.In this paper,aiming at...Cognitive Radio(CR) is a promising technique for the next generation mobile communi-cation system for its capability to solve the conflicts between the scarcity and underutilization of spectrum.In this paper,aiming at maximizing the system capacity of a multi-antenna CR system on the premise that avoid interference to the primary system in the same band simultaneously,a resource allocation method which is able to avoid interference between PRimary(PR) and CR users by pro-jecting the transmit signals of CR users on the null space of the PR users' channels is proposed.CR users with better channel condition are selected,and the interference from CR system to PR users can be removed completely by projecting the transmit signals of CR system on the null-space of PR users' channels.Parallel sub-channels are constructed for CR users through Singular Value Decomposition(SVD).At last,waterfilling is also adopted to increase the CR users' capacity.Simulation result demonstrates that compared with existing methods,our method can improve the achievable sum rate of CR users as well as reduce the outage probability of PR users.展开更多
Coordinated multi-point transmission and reception (CoMP) scheme enable LTE-Advanced systems to achieve their higher spectral efficiency. Allowing base stations to cooperate one another is one of the solutions to miti...Coordinated multi-point transmission and reception (CoMP) scheme enable LTE-Advanced systems to achieve their higher spectral efficiency. Allowing base stations to cooperate one another is one of the solutions to mitigate the inter-cell interference (ICI). In this paper, we propose an iterative power allocation scheme with MMSE procoding based on a modified water-filling for downlink CoMP systems, which achieves the optimal performance. The simulation results show that our proposed system can achieve its optimal rate according to its antenna configuration. Comparing them with a block diagonalization (BD) shows the advantages of MMSE precoding, in particular at a low SNR region.展开更多
基金supported by the National Natural Science Foundation of China under Grant 60372055the National High Technology Research and Development program of China under Grant 2006AA01Z262
文摘Aiming at the problem of resource allocation in multiuser multi-input multi-output (MIMO)systems,a new power allocation algorithm based on dual waterfilling is proposed.Block diagonalization is adopted to cancel the inter-user interference,and then the complete diagonalization method is employed to derive the spatial sub-channels for each user.The overall power of the system is divided among users based on each user’s large scale fading;then the power of each user is further allocated to its spatial sub-channels based on the small scale fading.Simulation results show that compared with the existing resource allocation strategies,the proposed algorithm can provide more ergodic capacity for multi-user MIMO systems.When the total transmit power is 100w,it has 15%capacity advantage over the traditional waterfilling method.
文摘Cognitive Radio(CR) is a promising technique for the next generation mobile communi-cation system for its capability to solve the conflicts between the scarcity and underutilization of spectrum.In this paper,aiming at maximizing the system capacity of a multi-antenna CR system on the premise that avoid interference to the primary system in the same band simultaneously,a resource allocation method which is able to avoid interference between PRimary(PR) and CR users by pro-jecting the transmit signals of CR users on the null space of the PR users' channels is proposed.CR users with better channel condition are selected,and the interference from CR system to PR users can be removed completely by projecting the transmit signals of CR system on the null-space of PR users' channels.Parallel sub-channels are constructed for CR users through Singular Value Decomposition(SVD).At last,waterfilling is also adopted to increase the CR users' capacity.Simulation result demonstrates that compared with existing methods,our method can improve the achievable sum rate of CR users as well as reduce the outage probability of PR users.
文摘Coordinated multi-point transmission and reception (CoMP) scheme enable LTE-Advanced systems to achieve their higher spectral efficiency. Allowing base stations to cooperate one another is one of the solutions to mitigate the inter-cell interference (ICI). In this paper, we propose an iterative power allocation scheme with MMSE procoding based on a modified water-filling for downlink CoMP systems, which achieves the optimal performance. The simulation results show that our proposed system can achieve its optimal rate according to its antenna configuration. Comparing them with a block diagonalization (BD) shows the advantages of MMSE precoding, in particular at a low SNR region.
