The demand for wireless data has been driving network capacity to double about every two years for the past 50 years, if not 100 years, and this has come to be known as Cooper＇s Law. In recent years, this trend has a...The demand for wireless data has been driving network capacity to double about every two years for the past 50 years, if not 100 years, and this has come to be known as Cooper＇s Law. In recent years, this trend has accelerated as a greater proportion of the population adopts wireless devices with ever greater capabilities, including tablets that support HD video and other advanced capabilities.展开更多
With the intensive deployment of users and the drastic increase of traffic load, a millimeter wave （mmWave） backhaul network was widely investigated. A typical mmWave backhaul network consists of the macro base stat...With the intensive deployment of users and the drastic increase of traffic load, a millimeter wave （mmWave） backhaul network was widely investigated. A typical mmWave backhaul network consists of the macro base station （MBS） and the small base stations （SBSs）. How to efficiently associate users with the MBS and the SBSs for load balancing is a key issue in the network. By adding a virtual power bias to the SBSs, more users can access to the SBSs to share the load of the MBS. The bias values shall be set reasonably to guarantee the backhaul efficiency and the quality of service （QoS）. An improved Q-learning algorithm is proposed to effectively adjust the bias value for each SBS. In the proposed algorithm, each SBS becomes an agent with independent learning and can achieve the best behavior, namely the optimal bias value through a series of training. Besides, an improved behavior selection mechanism is adopted to improve the learning efficiency and accelerate the convergence of the algorithm. Finally, simulations conducted in the 60 GHz band demonstrate the superior performance of the proposed algorithm in backhaul efficiency and user outage probability.展开更多
Hybrid beamforming（ HBF） technology becomes one of the key technologies in the millimeter wave（ mm Wave）mobile backhaul systems,for its lower complexity and low power consumption compared to full digital beamform...Hybrid beamforming（ HBF） technology becomes one of the key technologies in the millimeter wave（ mm Wave）mobile backhaul systems,for its lower complexity and low power consumption compared to full digital beamforming（ DBF）. Two structures of HBF exist in the mm Wave mobile backhaul system,namely,the fully connected structures（ FCS） and partially connected structures（ PCS）. However,the existing methods cannot be applied to both structures. Moreover,the ideal phase shifter is considered in some current HBF methods,which is not realistic. In this paper,a HBF algorithm for both structures based on the discrete phase shifters is proposed in the mm Wave mobile backhaul systems. By using the principle of alternating minimization,the optimization problem of HBF is decomposed into a DBF optimization problem and an analog beamforming（ ABF） optimization problem.Then the least square（ LS） method is enabled to solve the optimization model of DBF. In addition,the achievable data rate for both structures with closed-form expression which can be used to convert the optimization model into a single-stream beamforming optimization model with per antenna power constraint is derived. Therefore,the ABF is easily solved. Simulation results show that the performance of the proposed HBF method can approach the full DBF by using a lower resolution phase shifter.展开更多
文摘The demand for wireless data has been driving network capacity to double about every two years for the past 50 years, if not 100 years, and this has come to be known as Cooper＇s Law. In recent years, this trend has accelerated as a greater proportion of the population adopts wireless devices with ever greater capabilities, including tablets that support HD video and other advanced capabilities.
基金supported by the State Major Science and Technique Project (MJ-2014-S-37)the 111 Project (B08038)
文摘With the intensive deployment of users and the drastic increase of traffic load, a millimeter wave （mmWave） backhaul network was widely investigated. A typical mmWave backhaul network consists of the macro base station （MBS） and the small base stations （SBSs）. How to efficiently associate users with the MBS and the SBSs for load balancing is a key issue in the network. By adding a virtual power bias to the SBSs, more users can access to the SBSs to share the load of the MBS. The bias values shall be set reasonably to guarantee the backhaul efficiency and the quality of service （QoS）. An improved Q-learning algorithm is proposed to effectively adjust the bias value for each SBS. In the proposed algorithm, each SBS becomes an agent with independent learning and can achieve the best behavior, namely the optimal bias value through a series of training. Besides, an improved behavior selection mechanism is adopted to improve the learning efficiency and accelerate the convergence of the algorithm. Finally, simulations conducted in the 60 GHz band demonstrate the superior performance of the proposed algorithm in backhaul efficiency and user outage probability.
基金supported by the State Major Science and Technique Project(MJ-2014-S-37)the National Natural Science Foundation of China(61201134)the 111 Project(B08038)
文摘Hybrid beamforming（ HBF） technology becomes one of the key technologies in the millimeter wave（ mm Wave）mobile backhaul systems,for its lower complexity and low power consumption compared to full digital beamforming（ DBF）. Two structures of HBF exist in the mm Wave mobile backhaul system,namely,the fully connected structures（ FCS） and partially connected structures（ PCS）. However,the existing methods cannot be applied to both structures. Moreover,the ideal phase shifter is considered in some current HBF methods,which is not realistic. In this paper,a HBF algorithm for both structures based on the discrete phase shifters is proposed in the mm Wave mobile backhaul systems. By using the principle of alternating minimization,the optimization problem of HBF is decomposed into a DBF optimization problem and an analog beamforming（ ABF） optimization problem.Then the least square（ LS） method is enabled to solve the optimization model of DBF. In addition,the achievable data rate for both structures with closed-form expression which can be used to convert the optimization model into a single-stream beamforming optimization model with per antenna power constraint is derived. Therefore,the ABF is easily solved. Simulation results show that the performance of the proposed HBF method can approach the full DBF by using a lower resolution phase shifter.
