A Low-Delay Low-Complexity EKF Design for Joint Channel and CFO Estimation in Multi-User Cognitive Communications

Parameter estimation in cognitive communications can be formulated as a multi-user estimation problem, which is solvable under maximum likelihood solution but involves high computational complexity. This paper presents a time-sharing and interference mitigation based EKF (Extended Kalman Filter) design for joint CFO (carrier frequency offset) and channel estimation at multiple cognitive users. The key objective is to realize low implementation complexity by decomposing highdimensional parameters into multiple separate low-dimensional estimation problems, which can be solved in a time-shared manner via pipelining operation. We first present a basic EKF design that estimates the parameters from one TX user to one RX antenna. Then such basic design is time-shared and reused to estimate parameters from multiple TX users to multiple RX antennas. Meanwhile, we use interference mitigation module to cancel the co-channel interference at each RX sample. In addition, we further propose adaptive noise variance tracking module to improve the estimation performance. The proposed design enjoys low delay and low buffer size (because of its online real-time processing), as well as low implementation complexity (because of time-sharing and pipeling design). Its estimation performance is verified to be close to Cramer-Rao bound

Adaptive Switching Between Single/Concurrent Link Scheme in Single Hop MIMO Networks

Concurrent link communications built on multi-antenna systems have been widely adopted for spatial resource exploitation. MIMA-MAC, a classical MIMO MAC protocol utilizing concurrent link scheme, is able to provide superior link throughput over conventional single link MAC (under certain isolated link topologies). However, when utilizing rich link adaptation functions in MIMO systems, there exists a non-ignorable probability that MIMA-MAC's throughput will be lower than that of single link scheme (such probability is dominated by the statistics of instantaneous link topology and channel response). Inspired by this critical observation, and for adapting to various link topologies, this paper will present a novel MAC design that can adaptively switch between single or concurrent link scheme. With the aim of absolutely outperforming the single link MAC, here our optimization criterion is to guarantee a throughput result that is either better than or at least equal to single link MAC's counterpart. To highlight the design rationale, we first present an idealized implementation having network information perfectly known in a non-causal way. Then for realistic applications, we further develop a practical MAC implementation dealing with realistic system impairments (distributed handshaking and imperfect channel estimation). Simulation results validate that link throughput in our MAC is higher than or equal to single link MAC's counterpart with minimized outage probabilities. And for ergodic link throughput, our proposed MAC can outperform the single link MAC and MIMA-MAC by around 20{%}-30{%}