New Interference Estimation for Power Control in Wireless Networks

This paper proposes new interference estimation for power control in broadband wireless data networks. The proposed approach gives the filtered interference power in real-time removing undesired effects such as the fluctuation of interference power and the measurement noise due to receiver noise. The well-known Finite Impulse Response （FIR） structure filter is adopted for both the interference and the noise covarianee estimation. The proposed mechanism provides both the filtered interference power and the filtered number of active co-channel interferers, which shows good inherent properties. And the filtered interference power is not affected by the constant number of active co-channel interferes. It is also shown that the filtered number of active co-channel interference is separated from the filtered interference power. From discussions about the choice of design parameters such as window length and eovariance ratio, they can make the estimation performance of the proposed FIR filtering based mechanism as good as possible. Via extensive computer simulations, the performance of the proposed mechanism is shown to be superior to the existing Kalman filtering based mechanism.

INTERFERENCE ESTIMATION AND ITS APPLICATIONS IN COGNITIVE RADIO NETWORKS

Cognitive Radio(CR) has been proposed as a system-level means to improve the spectrum utilization efficiency.The most significant premise for CR networks is to avoid harmful interference to the licensed users.Therefore,it is very important to estimate the potential inter-ference introduced by the deployment of CR networks so that CR networks can be coexistence with Licensed User(LU) networks by designing proper system parameters.In this paper,two statistical models of potential interference due to CR networks are developed based on transmitter and receiver oriented spectrum sensing schemes,respectively.The approximate probability dis-tributions of aggregate interference introduced by CR networks are then derived with respect to the obtained models.With the help of these probability distributions,a method is further pre-sented to get the critical system parameter,i.e.,sensing distance and user density of the CR networks,so that the introduced interference can be controlled to predefined level.Numerical results validate the proposed interference estimation method and confirm the effectiveness of in-terference distribution based system parameter design.

A Particle Filter of Blind Equalization and Multiuser Detection in Asynchronous DS/CDMA Systems

The particle filter （PF） is proposed to be the asynchronous direct-sequence code-division multiple-access （DS/CDMA） multiuser detector without knowing the channel state information. The PF performs symbol detection according to the joint posterior density probability of simulated particles including relative delays, fading gains and symbols via sequential importance sample and resample. A simplified scheme is also proposed by separating the indepent relative delays and fading with symbols. These parameters are modeled as the extended aggressive processes and estimated by the Kalman filter, so as to provide their arbitrary distribution for symbol detection. Simulation results show that the bit error rate of the PF is less than conventional detectors. Moreover, the complexity of PF is moderate comparable to other nonlinear suboptimal approaches.

Semiparametric theory based MIMO model and performance analysis

In this article, a new approach for modeling multiinput multi-output （MIMO） systems with unknown nonlinear interference is introduced. The semiparametric theory based MIMO model is established, and Kernel estimation is applied to combat the nonlinear interference. Furthermore, we derive MIMO capacity for these systems and explore the asymptotic properties of the new channel matrix via theoretical analysis. The simulation results show that the semiparametric theory based modeling and kernel estimation are valid to combat this kind of interference.