Massive MIMO systems offer a high spatial resolution that can drastically increase the spectral and/or energy efficiency by employing a large number of antennas at the base station(BS).In a distributed massive MIMO sy...Massive MIMO systems offer a high spatial resolution that can drastically increase the spectral and/or energy efficiency by employing a large number of antennas at the base station(BS).In a distributed massive MIMO system,the capacity of fiber backhaul that links base station and remote radio heads is usually limited,which becomes a bottleneck for realizing the potential performance gain of both downlink and uplink.To solve this problem,we propose a joint antenna selection and user scheduling which is able to achieve a large portion of the potential gain provided by the massive MIMO array with only limited backhaul capacity.Three sub-optimal iterative algorithms with the objective of sumrate maximization are proposed for the joint optimization of antenna selection and user scheduling,either based on greedy fashion or Frobenius-norm criteria.Convergence and complexity analysis are presented for the algorithms.The provided Monte Carlo simulations show that,one of our algorithms achieves a good tradeoff between complexity and performance and thus is especially fit for massive MIMO systems.展开更多
In this paper, the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analysed through a statistical-mechanical appr...In this paper, the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analysed through a statistical-mechanical approach. Replica analyses focus on analytically studying how the minimum mean square error （MMSE） channel estimation error appears in a multiuser channel capacity formula. And the relevant mathematical expressions are derived. At the same time, numerical simulation results are demonstrated to validate the Replica analyses. The simulation results show how the system parameters, such as channel estimation error, system load and signal-to-noise ratio, affect the channel capacity.展开更多
In this paper,the transmission performances are studied in cognitive radio networks with primary user emulator and relay existence.In the proposed network,the users include primary users,secondary users and primary us...In this paper,the transmission performances are studied in cognitive radio networks with primary user emulator and relay existence.In the proposed network,the users include primary users,secondary users and primary user emulators.The decreasing access priority of the users are primary users,primary user emulators and secondary users.Different user access to the network results in different transmission effects.We impose interference power constraints on the secondary users to protect the primary users from being interfered.We also adopt the transmission mechanism that transits among more than one secondary transmitters,secondary receivers and relays.The transition models of the transmission states are proposed to describe the transmission mechanism.To investigate the transmission performances,the theory of effective capacity is adopted.The transmission performances in terms of effective capacity are expressed and demonstrated under different transmission policies.The overall effective capacity,as the overall data traffic in the cognitive radio network,is calculated.Besides,the overall effective capacity is demonstrated under different transmission strategies.The results show the greedy transmission strategy outperforms the rest of the transmission 8 policies in the overall effective capacity.For a larger number of the users,the effective capacity converges to a certain value.展开更多
基金supported in part by National Natural Science Foundation of China No.61171080
文摘Massive MIMO systems offer a high spatial resolution that can drastically increase the spectral and/or energy efficiency by employing a large number of antennas at the base station(BS).In a distributed massive MIMO system,the capacity of fiber backhaul that links base station and remote radio heads is usually limited,which becomes a bottleneck for realizing the potential performance gain of both downlink and uplink.To solve this problem,we propose a joint antenna selection and user scheduling which is able to achieve a large portion of the potential gain provided by the massive MIMO array with only limited backhaul capacity.Three sub-optimal iterative algorithms with the objective of sumrate maximization are proposed for the joint optimization of antenna selection and user scheduling,either based on greedy fashion or Frobenius-norm criteria.Convergence and complexity analysis are presented for the algorithms.The provided Monte Carlo simulations show that,one of our algorithms achieves a good tradeoff between complexity and performance and thus is especially fit for massive MIMO systems.
基金Project supported by the National Nature Science Foundation of China (Grant Nos 60773085 and 60801051)
文摘In this paper, the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analysed through a statistical-mechanical approach. Replica analyses focus on analytically studying how the minimum mean square error （MMSE） channel estimation error appears in a multiuser channel capacity formula. And the relevant mathematical expressions are derived. At the same time, numerical simulation results are demonstrated to validate the Replica analyses. The simulation results show how the system parameters, such as channel estimation error, system load and signal-to-noise ratio, affect the channel capacity.
基金supported by National Natural Science Foundation of China(No.61379016)
文摘In this paper,the transmission performances are studied in cognitive radio networks with primary user emulator and relay existence.In the proposed network,the users include primary users,secondary users and primary user emulators.The decreasing access priority of the users are primary users,primary user emulators and secondary users.Different user access to the network results in different transmission effects.We impose interference power constraints on the secondary users to protect the primary users from being interfered.We also adopt the transmission mechanism that transits among more than one secondary transmitters,secondary receivers and relays.The transition models of the transmission states are proposed to describe the transmission mechanism.To investigate the transmission performances,the theory of effective capacity is adopted.The transmission performances in terms of effective capacity are expressed and demonstrated under different transmission policies.The overall effective capacity,as the overall data traffic in the cognitive radio network,is calculated.Besides,the overall effective capacity is demonstrated under different transmission strategies.The results show the greedy transmission strategy outperforms the rest of the transmission 8 policies in the overall effective capacity.For a larger number of the users,the effective capacity converges to a certain value.
