Analysis of the Multistage CM Array/Signal Canceler for Digital Communication Signals

Abstract

The multistage constant modulus (CM) array is a blind adaptive beamformer that can separate cochannel digital communication signals. It consists of several identical stages connected in a cascade structure. Each stage is composed of a multichannel linear equalizer (MCLE) and a multichannel signal canceler (MCSC). The MCLE generates a linear estimate of one cochannel signal impinging on the antenna array. This captured source is removed from the input by the MCSC, which is a parallel connection of adaptive FIR filters, one for each antenna element. In this paper, we describe the architecture of the multistage CM array/signal canceler, and derive the Wiener weights for the MCLE and the MCSC. A discrete-time channel model with fractional sampling at the antenna array is employed. It is demonstrated that the power of the source captured by the first stage is reduced to the noise floor at the input of the next stage, whereas the other sources pass through essentially unchanged. Computer simulations are presented to illustrate the capture behavior of the multistage system.

Indexing terms:

• Adaptive arrays
• Adaptive equalizers
• Adaptive signal processing
• Cochannel interference
• Communication systems
• Least-mean-square methods

Additional information

Notes on contributors

Arvind V Keerthi

Arvind V Keerthi born in Madras, India, on May 10, 1971. He received the BTech degree in electrical engineering from the Indian Institute of Technology, Bombay, in 1992, and the M S and PhD degrees in electrical and computer engineering from the University of California, Santa Barbara, in 1993 and 1997, respectively. Since October 1997, he has been employed with QUALCOMM Inc, in San Diego, CA.

At UCSB, he addressed the problem of cochannel signal separation for a variety of wireless standards such as AMPS, North American TDMA, and GSM. At QUALCOMM, he is on a team that designs modems for CDMA base stations. His current interests are adaptive antennas and communication theory.

John J Shynk

John J Shynk received the BS degree in Systems Engineering from Boston University, Boston, MA, in 1979, the MS degree in electrical engineering and in statistics, and the PhD degree in electrical engineering from Stanford University, Stanford, CA, in 1880, 1985, and 1987, respectively. From 1979 to 1982, he was a Member of Technical Staff in the Data Communications Performance Group at AT&T Bell Laboratories, Halmdel, NJ, where he formulated performance models for voiceband data communications. He was a Research Assistant from 1982 to 1986 in the Department of Electrical Engineering at Stanford University where he worked on frequency-domain implementations of adaptive MR filter algorithms. From 1985 to 1986, he was also an Instructor at Stanford University, teaching courses on digital signal processing and adaptive systems. Since 1987, he has been with the Department of Electrical and Computer Engineering at the University of California, Santa Barbara, where he is currently a Professor.

His research interests include adaptive signal processing, adaptive beamforming, wireless communications, and direction-of-arrival estimation. He served as an Associate Editor for adaptive filtering for the IEEE Transactions on Singal processing, an Editor for adaptive signal processing for the International Journal of Adaptive Control and Signal Processing, and an Associate Editor for the IEEE Singal Processing Letters. Dr Shynk was Technical Program Chair of the 1992 International Joint Conference on Neural Networks. He is a member of the IEEE Signal Processing for Communications Technical Committee.