Performance of beamforming and mimo technique in an indoor ricean clustering channel

In this paper, we present a hybrid indoor MIMO channel model for predicting the performance of multiple-element antenna system. The model incorporates the wave clustering phenomena and combines the statistical characteristics of clusters with deterministic ray tracing method. The capacity of the MIMO channel is expressed as a function of spatial correlation at both the transmitter and the receiver. The results obtained by using the channel model are compared with measurement results available in the literature. Simulation results verify that the MIMO technique effectively exploits multipath fading. The paper also presents a comparison between MIMO and beamforming techniques in indoor environments

Experimental investigation of indoor MIMO Ricean channel capacity

We investigate the variation of measured multiple-input multiple-output (MIMO) channel capacity for line-of-sight (LOS) Ricean scenarios inside a typical indoor environment for various transmitter-receiver positions at a center frequency of 2.45 GHz. In order to quantify the effect of LOS component on indoor MIMO performance, an absorber-loaded metal panel was utilized to artificially obstruct the LOS path between the transmit and receive antennas. Our results confirm that MIMO capacity decreases with the increase in the values of Ricean K factor. We have also observed that the variation in channel capacity closely follows the corresponding deviations in root mean square (rms) delay spread of the channel. © 2005 IEEE

Continuous variable entanglement measurement without phase locking

A new simple entanglement measurement method is proposed for the bright EPR beams generated from a non-degenerate optical parametric amplifier operating at deamplification. Due to the output signal and idler modes are frequency degenerate and in phase, the needed phase shift of interference for the measurement of the correlated phase quadratures and anti-correlated amplitude quadratures can be accomplished by a quarter-wave plate and a half wave plate without separating the signal and idler beam. Therefore, phase locking and local oscillators are avoided.Comment: 8 pages,3 figure

Indoor Multipath Characterization for MIMO Wireless Communications

The achievable linear increase in multiple-input multipleoutput (MIMO) capacity is conditioned on sufficiently rich multipath" presenting in a wireless channel. Thus, the characterization of the resolvable multipaths in an indoor environment dictates the obtainable MIMO capacity at a certain SNR level. In this paper, the statistic relationship between the characteristics of multipaths and the performance of MIMO systems in indoor environments is explored using channel measurements. Our investigations demonstrate the terminology of richness, which is generally used to characterize the multipath propagation, highly relates to the number of effective multipaths, their carried power and their angular features. A novel dimensionless parameter, angular spread factor, is proposed in this work.

A memetic algorithm with adaptive hill climbing strategy for dynamic optimization problems

Copyright @ Springer-Verlag 2008Dynamic optimization problems challenge traditional evolutionary algorithms seriously since they, once converged, cannot adapt quickly to environmental changes. This paper investigates the application of memetic algorithms, a class of hybrid evolutionary algorithms, for dynamic optimization problems. An adaptive hill climbing method is proposed as the local search technique in the framework of memetic algorithms, which combines the features of greedy crossover-based hill climbing and steepest mutation-based hill climbing. In order to address the convergence problem, two diversity maintaining methods, called adaptive dual mapping and triggered random immigrants, respectively, are also introduced into the proposed memetic algorithm for dynamic optimization problems. Based on a series of dynamic problems generated from several stationary benchmark problems, experiments are carried out to investigate the performance of the proposed memetic algorithm in comparison with some peer evolutionary algorithms. The experimental results show the efficiency of the proposed memetic algorithm in dynamic environments.This work was supported by the National Nature Science Foundation of China (NSFC) under Grant Nos. 70431003 and 70671020, the National Innovation Research Community Science Foundation of China under Grant No. 60521003, and the National Support Plan of China under Grant No. 2006BAH02A09 and the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01

A particle swarm optimization based memetic algorithm for dynamic optimization problems

Copyright @ Springer Science + Business Media B.V. 2010.Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic. This paper investigates a particle swarm optimization (PSO) based memetic algorithm that hybridizes PSO with a local search technique for dynamic optimization problems. Within the framework of the proposed algorithm, a local version of PSO with a ring-shape topology structure is used as the global search operator and a fuzzy cognition local search method is proposed as the local search technique. In addition, a self-organized random immigrants scheme is extended into our proposed algorithm in order to further enhance its exploration capacity for new peaks in the search space. Experimental study over the moving peaks benchmark problem shows that the proposed PSO-based memetic algorithm is robust and adaptable in dynamic environments.This work was supported by the National Nature Science Foundation of China (NSFC) under Grant No. 70431003 and Grant No. 70671020, the National Innovation Research Community Science Foundation of China under Grant No. 60521003, the National Support Plan of China under Grant No. 2006BAH02A09 and the Ministry of Education, science, and Technology in Korea through the Second-Phase of Brain Korea 21 Project in 2009, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01 and the Hong Kong Polytechnic University Research Grants under Grant G-YH60