Matrix computations (3rd ed.)
Pilot-Assisted Carrier Frequency Offset Estimation for MIMO-OFDM Systems
CIT '04 Proceedings of the The Fourth International Conference on Computer and Information Technology
Intercarrier interference in MIMO OFDM
IEEE Transactions on Signal Processing
FSF MUSIC for Joint DOA and Frequency Estimation and Its Performance Analysis
IEEE Transactions on Signal Processing
TST-MUSIC for joint DOA-delay estimation
IEEE Transactions on Signal Processing
A low-complexity space-time OFDM multiuser system
IEEE Transactions on Wireless Communications
Frequency Offset Estimation and Training Sequence Design for MIMO OFDM
IEEE Transactions on Wireless Communications
IEEE Transactions on Information Theory
Modeling the statistical time and angle of arrival characteristics of an indoor multipath channel
IEEE Journal on Selected Areas in Communications
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Due to the popularity of IEEE 802.11a/g/n wireless local area networks, the high-density deployment of access points and their serious mutual interference have become a pressing concern, and made both frequency acquisition and data detection even more difficult. In addition, improving the network coverage and scalability in the mesh mode of IEEE 802.16 wireless metropolitan area network, space and frequency information can provide abundant scheduling information under the configuration. In light of this, this paper presents an antenna-array-assisted algorithm to solve these two problems in a multiuser multiple-input-multiple-output orthogonal frequency division multiplexing interference network. The algorithm begins with the estimation of three channel parameters: frequency offsets, delays and angle selectivity. To make a good use of the array signal characteristics, these three parameters are estimated in a frequency/delay-angle-frequency/delay (FAF) tree structure, in which two frequency/delay estimations and one angle estimation are employed alternatively. One special feature in the FAF tree structure is that temporal filtering or spatial beamforming is invoked between the parameter estimations to decompose signals so as to enhance the estimation accuracy. Thereafter, based on these parameter estimates, a data detection procedure is developed to mitigate both multiple access interference (MAI) and co-channel interference (CCI). Simulations show that the proposed algorithm can provide satisfactory performance even in networks with MAIs and CCIs sharing the same frequency band.