Effect of Mutual Coupling on the Interference Rejection Capabilities of Linear and Circular Arrays in CDMA Systems

Abstract

Abstract-This paper is concerned with assessing the interference rejection capabilities of linear and circular array of dipoles that can be part of a base station of a code-division multiple-access cellular communication system. The performance criteria for signal-to-interference ratio (SIR) improvement employed in this paper is the spatial interference suppression coefficient. We first derive an expression for this figure of merit and then analyze and compare the SIR performance of the two types of arrays. For a linear array, we quantitatively assess the degradation in SIR performance as we move from array broadside to array end-fire direction. In addition, the effect of mutual coupling is taken into account.

Performance Analysis of Antenna Array Beamformers With Mutual Coupling Effects

“…The effect of MC is taken into account by using a distortion matrix model [8][9][10][11][12][13][14]. According to this model, we insert a mutual coupling matrix (MCM) C in the data model for the received signal as follows:…”

“…For all simulation examples, we adopt the MCM C suggested by [11,12,14,15] as follows: where Z A is the sensor's impedance in isolation, Z T is the impedance of the receiver at each sensor and is set to the complex conjugate of Z A to achieve an impedance match for maximum power transfer. Consider the case of an antenna array with the side-by-side configuration and the dipole length = λ/2, where λ is the wavelength of signal sources.…”

“…Consider the case of an antenna array with the side-by-side configuration and the dipole length = λ/2, where λ is the wavelength of signal sources. Then, Z is the mutual impedance matrix given by [11,12,14,15] …”

“…All signals received by an antenna array are affected by MC and the data will be no longer independent. The MC between the array sensors can significantly change an antenna array's behavior and its communication characteristics [9][10][11][12]. The predicted array system performances may not be accurate when we ignore the MC effects.…”

“…According to this model, we insert a mutual coupling matrix (MCM) in the data model for the signal received by an array beamformer. Each entry of the MCM represents the MC coefficient between two related array sensors and can be estimated from collected measurement data [11,12,14,15]. We first investigate the performance of the LCMV beamformers which are widely applied for achieving beamforming with various goals [16][17][18][19][20][21].…”