Vehicular Ad Hoc Network (VANET) is an emerging field of technology that allows vehicles to communicate together in the absence of fixed infrastructure. The basic premise of VANET is that in order for a vehicle detect other vehicles in the vicinity. This cognizance, awareness of other vehicles, can be achieved through beaconing. In the near future, many VANET applications will rely on beaconing to enhance information sharing. Further, the uneven distribution of vehicles, ranging from dense rush hour traffic to sparse late night volumes creates a pressing need for an adaptive beaconing rate control mechanism to enable a compromise between network load and precise awareness between vehicles. To this end, we propose an intelligent Adaptive Beaconing Rate (ABR) approach based on fuzzy logic to control the frequency of beaconing by taking traffic characteristics into consideration. The proposed ABR considers the percentage of vehicles traveling in the same direction, and status of vehicles as inputs of the fuzzy decision making system, in order to tune the beaconing rate according to the vehicular traffic characteristics. To achieve a fair comparison with fixed beaconing schemes, we have implemented ABR approach in JIST/SWANs. Our simulation shows that the proposed ABR approach is able to improve channel load due to beaconing, improve cooperative awareness between vehicles and reduce average packet delay in lossy/lossless urban vehicular scenarios.
The problem of designing Joint Power Control and Optimal Beamforming (JPCOB) algorithms for the downlink of a coordinated multi-cell W-CDMA system is considered throughout this paper. In this case, the JPCOB design is formulated as the problem of minimizing the total transmitted power in the coordinated multi-cell system, subject to a certain quality of service requirement for each user. In this paper, the performance of two JPCOB algorithms based on different beamforming approaches is compared over the coordinated multi-cell system. The first one, obtains local beamformers by means of the well-known virtual uplink-downlink duality. In contrast, the second algorithm implements multi-base beamformers, taking into account match filter equalizers at the receivers. Moreover, realistic system parameters, such as per-base station power constraints or the asynchronous nature of the signals arriving at the receivers, are taken into account. Simulation results show that the algorithm based on multi-base beamforming presents attractive properties, such as an inherent multi-base scheduling technique or a decreasing total transmitted power as the degree of coordination between base stations is increased. Index Terms-Coordinated multi-cell system, downlink multibase beamforming, multi-base scheduling techniques, joint power control and optimal beamforming algorithms.
Abstract-Adaptive filtering schemes exhibit a compromise between convergence speed and steady-state mean square error. Convex combination approaches that provide meaningful performance have been recently developed for system identification. The purpose of this work is to apply the convex combination strategy to multichannel active noise control systems, taking into account the secondary path between the adaptive filter output and the error sensor and the eventual unavailability of the disturbance signal, which depends on the filtering scheme considered. Even though this strategy involves a computational burden higher than the classic adaptive filters, it exhibits optimum performance in term of convergence speed and steady-state mean square error.
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