Blind Maximum Likelihood Interference Mitigation for PDCCH of 3GPP LTE/LTE-A

Abstract

The performance of the downlink physical channels of 3GPP LTE/LTE-A system is typically limited by co-channel interference from neighboring cells. Therefore, the development of efficient algorithms for interference mitigation at the mobile receiver has recently attracted a lot of attention in academia and industry. There have been a number of studies on advanced interference cancellation and suppression techniques for the physical downlink shared channel (PDSCH) of LTE/LTE A carrying data packets to the users. One of the most promising schemes identified for demodulation of PDSCH is the maximum likelihood (ML) receiver. It was shown by link-level analysis that the joint ML detection of serving and interfering signals can provide performance improvement. Due to its performance benefits, the ML receiver should be also considered for demodulation of other downlink channels including the physical downlink control channel (PDCCH) which carries downlink and uplink scheduling assignments. However, a number of issues specific only to PDCCH could make problematic the use of the conventional ML receiver designed for PDSCH. More specifically, transparent power control on PDCCH (i.e., without network signaling to the user) at both serving and interfering cells as well as random interference hit from PDCCH transmissions of interfering cells may result to non-negligible performance degradation of PDCCH when the conventional ML receiver is used. Therefore, in this paper we propose an enhanced ML receiver for the PDCCH with the ability of blind power boosting estimation and interference hit detection. Using link-level simulations it is shown that in interference limited scenarios the proposed ML receiver provides remarkable error rate improvements for PDCCH over the conventional ML and linear receivers such as Maximum Ratio Combining (MRC) and Enhanced Minimum Mean-Squared Error with Interference Rejection Combining (E-MMSE-IRC).