Considering the dynamic changes and uncertainty features of the radio environment in cognitive wireless networks(CWNs),the environment cognition ability is critical for the performance evaluation of CWNs design and optimization.However,there are no effective metrics to evaluate the ability and gain of information cognition in CWNs from an information theory perspective.Therefore,the novel cognitive information concept is proposed and defined as a metric to evaluate the uncertainty of both the internal and external environments of one system that can be removed by other systems or nodes using cognitive radio techniques.As an intelligent wireless communication system that is aware of its surrounding radio,network,and user multi-domains environment,the more cognitive information it achieves,the higher level cognitive capability it is.In this paper,we define and analyze the mathematical features of cognitive information.Results reveal that the increase of cognitive information can improve the spectrum efficiency and reduce the interference probability simultaneously in CWNs.Thus cognitive information can be regarded as a metric for CWNs optimization.Finally,we apply the theory of cognitive information in the parameters optimization in energy detection and cooperative spectrum sensing.
Two-dimensional(2D) multiple-input multiple-output(MIMO) is currently concentrated on propagation in horizontal plane, but the impact of elevation angle is not considered. However, due to the three-dimensional(3D) character of the real MIMO channel, 2D MIMO cannot achieve the optimal system throughput. A multiple-user MIMO(MU-MIMO) user pairing scheme was proposed, in which the vertical dimension was taken into consideration. In the proposed scheme, a 3D codebook based on full dimension MIMO channel was designed; then two 3D MU-MIMO user's pairing schemes are proposed combining the proposed joint and separate 3D codebook. Simulation evaluates the proposed 3D codebook aided user pairing scheme and compares with the previous 2D MU-MIMO user pairing technology. Owing to the additional spatial degree of freedom in vertical dimension, the proposed 3D MU-MIMO user pairing schemes can effectively improve the overall system performance.
This paper presents a novel interference management strategy, to adaptively choose the best fractional frequency reuse (FFR) scheme for macro and femto networks. The strategy aims to maximize the system throughput taking into account a number of system constraints. Here, the system constrains consist of the outage constraints of two-tier users and macrocell spectral efficiency requirement. The detailed procedures of our proposed strategy are: 1) A reference signal received power (RSRP) based selection algorithm is presented to adaptively select the optional FFR schemes satisfying the outage constraints. 2) Considering the macrocell spectral efficiency, the optimal FFR scheme is selected from the optional FFR schemes at MeNB side, to achieve the maximum system throughput in two-tier femtocell networks. We study the efficacy of the proposed strategy using an long term evolution advanced (LTE-A) system level simulator. Simulation results show that our proposed interference management strategy can select the best FFR scheme to maximize the system throughput, and the FFR schemes derived by using RSRP-based selection algorithm can be the effective solutions to deploy femtocells in macrocells.
