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GLOBECOM
2007
IEEE
14 years 1 months ago
Reduced Complexity Sphere Decoding for Square QAM via a New Lattice Representation
— Sphere decoding (SD) is a low complexity maximum likelihood (ML) detection algorithm, which has been adapted for different linear channels in digital communications. The comple...
Luay Azzam, Ender Ayanoglu
VTC
2007
IEEE
14 years 1 months ago
Fast and Area-Efficient Sphere Decoding Using Look-Ahead Search
— Sphere decoding enables maximum likelihood (ML) detection with fairly low complexity in the MIMO wireless systems, but it takes hundreds cycles at low SNR environment. This pap...
Se-Hyeon Kang, In-Cheol Park
TSP
2010
13 years 1 months ago
Low-complexity decoding via reduced dimension maximum-likelihood search
In this paper, we consider a low-complexity detection technique referred to as a reduced dimension maximum-likelihood search (RD-MLS). RD-MLS is based on a partitioned search which...
Jun Won Choi, Byonghyo Shim, Andrew C. Singer, Nam...
ICC
2007
IEEE
245views Communications» more  ICC 2007»
14 years 1 months ago
Low Complexity MMSE Vector Precoding Using Lattice Reduction for MIMO Systems
—In this paper, a lattice-reduction-aided (LRA) With such an approximation, the complexity of VP is greatly minimum mean square error (MMSE) vector precoding (VP) is reduced. pro...
Feng Liu, Ling-ge Jiang, Chen He
TSP
2008
101views more  TSP 2008»
13 years 6 months ago
Subspace-Based Algorithm for Parameter Estimation of Polynomial Phase Signals
In this correspondence, parameter estimation of a polynomial phase signal (PPS) in additive white Gaussian noise is addressed. Assuming that the order of the PPS is at least 3, the...
Yuntao Wu, Hing Cheung So, Hongqing Liu