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We propose a semi-blind precoding aided maximum likelihood (ML) carrier frequency offset (CFO) estimation method and a precoding aided equalization based on independent component analysis (ICA) receiver structure for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) wireless communication systems. By carefully designing a constant in the precoding process, the...
We propose a received signal strength (RSS) based energy-efficient positioning approach for cellular networks with unknown path loss exponent (PLE). A low-complexity searching algorithm is proposed for PLE estimation and a low-complexity lateration algorithm is proposed to provide the searching criteria. Simulation results show that the proposed positioning method achieves an accuracy similar to that...
We propose a low-complexity frequency synchronization approach for semi-blind independent component analysis (ICA) based coordinated multi-point (CoMP) orthogonal frequency division multiplexing (OFDM) systems, with multiple carrier frequency offsets (CFOs). The key idea is to introduce a short pilot for both multi-CFO estimation and ambiguity elimination in the ICA equalized signals. First, by minimizing...
We propose a sparse probabilistic learning approach for nonlinear channel equalization in wireless communication systems, by using the relevant vector machine (RVM) technique. In particular, we propose two versions of the RVM based equalizer: 1) maximum a posterior RVM (MAP-RVM), 2) marginalized RVM (MRVM). Compared to the standard support vector machine (SVM) method, the proposed RVM approach not...
The genetic algorithm (GA) is a well studied technique, which can obtain efficiently a near-optimal solution with much lower computational complexity compared to the maximum likelihood detection (MLD) approach. In overloaded MIMO systems, since the number of near equal-power co-channel interferers is higher than the number of receive antennas, the interference cannot be completely removed by spatial...
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