Interference Cancellation, Channel Estimation, and Symbol Detection for Communications on Overlapping Channels

Abstract

In this paper, we propose the joint interference cancellation, fast fading channel estimation, and data symbol detection for a general interference setting where the interfering source and the interfered receiver are unsynchronized and occupy overlapping channels of different bandwidths. The interference must be canceled before the channel estimation and data symbol detection of the desired communication are performed. To this end, we have to estimate the Effective Interference Coefficients (EICs) and then the desired fast fading channel coefficients. We construct a two-phase framework where the EICs and desired channel coefficients are estimated using the joint maximum likelihood-maximum a posteriori probability (JML-MAP) criteria in the first phase; and the MAP based data symbol detection is performed in the second phase. Based on this two-phase framework, we also propose an iterative algorithm for interference cancellation, channel estimation and data detection. We analyze the channel estimation error, residual interference, symbol error rate (SER) achieved by the proposed framework. We then discuss how to optimize the pilot density to achieve the maximum throughput. Via numerical studies, we show that our design can effectively mitigate the interference for a wide range of SNR values, our proposed channel estimation and symbol detection design can achieve better performances compared to the existing method. Moreover, we demonstrate the improved performance of the iterative algorithm with respect to the non-iterative counterpart.

A Study on Enhancing Channel Estimation in Vehicular Communications: Metamaterial-Enhanced Microstrip Antennas

“…Hu et al [12] develop an iterative reweight-based super resolution channel estimation scheme, demonstrating superior performance compared to conventional methods. Nguyen et al [13] present a framework for interference cancellation, fast fading channel estimation, and data symbol detection in unsynchronized interference settings. Liu et al [14] investigate distributed estimation in wireless sensor networks with power constraints.…”