Article

# On Sum Rate and Power Consumption of Multi-User Distributed Antenna System with Circular Antenna Layout

EURASIP Journal on Wireless Communications and Networking (Impact Factor: 0.81). 01/2007; DOI: 10.1155/2007/89780

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**ABSTRACT:**We consider an extended wireless network with transmit and receive nodes distributed according to Bernoulli lattice processes in 1D and 2D spaces. The received signals are jointly processed at a central unit. The channel is characterized by pathloss attenuation depending on distances between transmit and receive antennas. We introduce a new class of Euclidean random matrix (ERM) to characterize the distributed antenna system (DAS). By leveraging on a suitable decomposition of these ERMs, we propose an approximated analysis of their spectra and use it to provide an analytical approximation of the capacity per unit area of the DAS.IEEE GLOBECOM 2014, Austin, USA; 12/2014 -
##### Conference Paper: Spectral Efficiency of Extended Networks with Randomly Distributed Transmitters and Receivers

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**ABSTRACT:**We consider an extended wireless network with transmit and receive nodes homogeneously distributed in R 2 . The channel state information (CSI) is known at the centralized processing unit at the receiver side but not at the transmitters which transmit at equal power. By extending the definition of Euclidean random matrices (ERM) and their spectral analysis to two independent sets of points, we determine an approximated expression of the average maximum achievable rate per unit area of the system.ChinaSIP 2014; 07/2014 - [Show abstract] [Hide abstract]

**ABSTRACT:**System capacity and antenna placement play crucial roles in wireless communication systems, and they are of great value to network planning. In this paper, we are motivated to analyze the system capacity and optimize the antenna placement in distributed antenna systems. This paper establishes a composite channel model which takes path loss, lognormal shadowing and Rayleigh fading into consideration. To reduce the computational complexity, an approximate theoretical expression of system capacity is derived with selective transmission at the transmitter and maximal ratio combining at the receiver. An antenna placement optimization problem is formulated, and then a genetic algorithm (GA) based searching scheme is proposed to solve the proposed optimization problem. The computational complexity analysis indicates that the proposed GA-based searching scheme is computationally efficient in terms of both running time and storage space. Numerical results show that the approximate theoretical expression of system capacity can provide a very good approximation to the simulation results, and the proposed GA-based searching scheme for solving the antenna placement optimization problem can consistently offer a large capacity gain over other existing schemes.Wireless Personal Communications 07/2013; 71(1). · 0.98 Impact Factor

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