An interference suppression scheme with joint channel-data estimation

Abstract

This paper describes an adaptive space-time receiver with joint channel-data estimation (JCDE) to combat time-varying multipath channels in the presence of undesired co-channel interference (CCI). The receiver uses a colored Gaussian metric for sequence detection in order to suppress the CCI. The proposed scheme also uses the knowledge of the transmit lter for improved channel estimation to enhance performance. The algorithm is derived as a quasi-Newton scheme on a chosen cost criterion and is also locally convergent. The performance of this class of interference cancellers is examined through the pairwise error probability (PEP). Through these expressions we gain insight into the properties of the canceller. The e ect of channel dynamics and identi cation mismatch on the PEP is also examined. To reduce implementational complexity, a hybrid delayed-decision feedback and JCDE scheme is also proposed. The performance is illustrated using numerical results in realistic transmission environments.

Great Expectations: The Value of Spatial Diversity in Wireless Networks

“…One way to exploit this is to allow multiple users to simultaneously transmit information and have multiple antennas at the receiver utilize spatial diversity when decoding the information. Therefore, since nature gives disparate channel signatures to the different users, this could be used to suppress interference using multiple antennas (for example, see [87] and references therein). In the sequel, we focus our attention on the use of multiuser spatial diversity (i.e., different channel signatures for different users), combined with space-time codes and how this structure can be utilized (without use of spreading codes) for multipacket reception.…”

An Improved Computational Model for Adaptive Communication Channel Estimation

“…The signal transmitted through the unknown channel is the desired training signal d(k), while the signal transmitted through the FIR filter output is the estimated training signal y(k). The two signals are transmitted through the summer to give the estimated error signal e(k).The estimated error signal is then used to update the coefficient of the FIR filter using the adaptation algorithm called Variable step size Partial Update Least Mean Square algorithm (VPU-LMS) [6].…”

“…The retrieval of information about the channel either from the received signal or from the signal sent is known as channel estimation. The major sources of impairment in wireless channels include channel time-variation, Inter Symbol Interference, and Co Channel Interference [6]. In order to deal with these problems, the transmitted signal needs to be processed at the receiver station.…”