Statistical interference

Abstract: Some impulse radio UWB (IR-UWB) networks may allow concurrent transmissions without power control (for example MAC protocols that do not use power control, or co-existing, non-coordinated piconets). In such cases, it has been proposed to mitigate multi-user interference (MUI) at the physical layer, but existing proposals for interference mitigation do not account for the multipath nature of UWB channels. We address this problem and propose a receiver that employs a combination of statistical interference modeling and thresholding to mitigate MUI. We find that in a multipath environment the proposed receiver significantly outperforms existing receiver designs that either completely neglect the effect of MUI or only use a simple threshold to reject samples from interfering users. Further, in contrast to successive interference cancellation schemes, our receiver does not require active decoding of each interferer. Thus there is no need to synchronize the receiver with all the interfering users, which would be impractical in an IR-UWB system that is likely to be run in ad hoc mode. To model MUI we consider a hidden Markov model (HMM) and a Gaussian mixture model (GMM). We find that the HMM models interference better than the GMM. However, the resulting performance difference is not huge and comes at the cost of increased receiver complexity.

Abstract: Several adaptive techniques are described to combat interference in multiple-input multiple-output (MIMO) systems. In addition to adaptive frequency selection, interference suppression techniques for a selected carrier frequency are presented. The interference suppression technique can be adaptively selected based on the availability and quality of channel state information (CSI) and interference statistics. Techniques to estimate interference statistics are also presented. Interference mitigation techniques are also presented for automatic gain control (AGC), intermittent interference, and interference caused to other networks.

Abstract: A centralized coordinated multipoint downlink joint transmission in a frequency division duplex system requires channel state information (CSI) to be fed back from the cell-edge users to their serving BS, and aggregated at the central coordination node for precoding, so that interference can be mitigated. The control signals comprising of CSI and the precoding weights can easily overwhelm the backhaul resources. Relative thresholding has been proposed to alleviate the burden; however, this is at the cost of reduction in throughput. In this paper, we propose utilizing the long-term channel statistics comprising of pathloss and shadow fading in the precoder design to model the statistical interference for the unknown CSI. In this regard, a successive second-order cone programming (SSOCP)-based precoder for maximizing the weighted sum rate is proposed. The accuracy of the solution obtained is bounded with the branch and bound technique. An alternative optimization framework via weighted mean square error minimization is also derived. Both these approaches provide an efficient solution close to the optimal, and also achieve efficient backhauling, in a sense that the precoding weights are generated only for the active links. For comparison, a stochastic approach based on particle swarm optimization is also considered.

Abstract: In this thesis, we develop an subcarrier transmission suboptimal power allocation algorithm and an underlay subcarrier transmission optimal power allocation algorithm for the orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems with different statistical interference constraints imposed by different primary users (PUs). Given the fact that the interference constraints are met in a statistical manner, the CR transmitter does not require the instantaneous channel quality feed- back from the PU receivers. First an alternative subcarrier transmission suboptimal algorithm with reduced complexity has been proposed and the performance has been investigated. Presented numerical results show that with our proposed suboptimal power allocation algorithm CR user can achieve 10 percent higher transmission capacity for given statistical interference constraints and a given power budget compared to the traditional suboptimal power allocation algorithms, uniform and water-filling power allocation algorithms. The proposed suboptimal algorithm outperforms traditional suboptimal algorithm, water-filling algorithm and uniform power loading algorithm. Second, We introduce an underlay subcarrier transmission optimal power allocation algorithms which allows the secondary users use the bandwidth used by Pus. And at the same time we consider the individual peak power constraint as the forth constraint added to the objective function which is the transmission capacity rate of the secondary users .Third, we propose suboptimal algorithm using GWF which has less complexity level than traditional water-filling algorithm instead of conventional water-filling algorithm in calculating the assigned power while considering the satisfaction of the total power constraint. The proposed suboptimal algorithm gives an option of using a low complexity power allocation algorithm where complexity is an issue.