Advanced Channel Parameter Estimation Techniques and Bounds for Next-Generation Wireless Networks

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Channel parameter estimation is a crucial task that lies at the heart of any wireless communication system. In fact, it allows the system to properly operate in complete awareness of its environment through the knowledge of its propagation channel. Within the framework of this discovery grant research program, we will consider the problem of wireless channel parameter estimation for various system configurations and signalling schemes that are geared toward current and future communication systems such as the new 4th-generation (4G) LTE-Advanced (LTE-A) wireless networks and beyond (LTE-B) as well as 5G. The key goal is to develop advanced channel identification and parameter estimation techniques and Cramer Rao lower bounds (CRLBs), preferably in closed-form, in the presence of various types of diversities; namely multi-path propagation, multiple receiving antennas, and multi-carrier communications combined with higher-order modulations (M-QAM). We will adopt a maximum likelihood (ML) approach to rip the full benefits of jointly exploiting these types of diversity. To significantly reduce complexity, we will recur to the new powerful importance sampling technique and global optimization principle to implement the ML approach. To increase spectrum efficiency, we will preferably develop non-data-aided (NDA) estimators or alternative data-aided (DA) versions that require the least pilot signal overhead. We will also investigate novel code-aided (CA) designs for turbo parameter estimation. To cope with short observation records in non-continuous packet-switched transmissions in non-persistent scheduling such as on the uplink of LTE-A, we will recur to the new powerful compressive sensing (CS) techniques.