Transmitter-assisted joint data-aided channel estimation and PAPR reduction scheme in wireless fading channels. [PDF]
Khan I, Hasan MM, Cheffena M.
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Micromachined mmWave 28.0/38.0 GHz MIMO antenna loaded with frequency selective surface for gain enhancement and SAR analysis for future wireless applications. [PDF]
Sharma M +6 more
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Weight optimization of MIMO-UWB distributed beamforming for implant communications. [PDF]
Kobayashi T +3 more
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Performance evaluation and validation of a quad-element super-wideband fractal MIMO antenna with integrated quad-band filtering capability for advanced 5G/IoT systems. [PDF]
Sohi AK +5 more
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Integrated approach for edge coverage enhancement based on IRS phase shift control and AP selection in dense user communication system. [PDF]
Shrivastava S +3 more
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Design and characterization of quad port dual band MIMO antenna for 5G V2X connectivity. [PDF]
Arumugam S +5 more
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Multiple Input Multiple Output (MIMO) Antennas
2023The advancement of antennas that can access high data speeds, and have higher gain, is largely responsible for the advancements in wireless technology. One such antenna called the multiple input multiple output (MIMO). This antenna has attracted the utmost attention of the researchers owing to its features like higher capacity, increased data rate, low
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Statistical characterization of multiple-input multiple-output (MIMO) channel capacity
2002 IEEE Wireless Communications and Networking Conference Record. WCNC 2002 (Cat. No.02TH8609), 2003We derive precise as well as good approximate statistical characterizations, such as probability density functions and statistical moments of capacity, for different MIMO wireless channels. The characterizations help us to understand and predict the capacity gain expected from the MIMO technique, in terms of system parameters and channel dimension.
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An energy-efficient multiple-input multiple-output (MIMO) detector architecture
2011 IEEE Workshop on Signal Processing Systems (SiPS), 2011In this paper, a novel low complexity energy efficient recon-figurable reduced dimension maximum likelihood (RRDML) multiple-input multiple-output (MIMO) detector is proposed. RRDML is based on RDML [1], in which maximum likelihood (ML) is applied to detect a sub-dimension of the received vector and linear detection is used for the remaining dimension.
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