Sudarshan Mukherjee

Low-Complexity CFO Estimation for Multi-User Massive MIMO Systems

Low-complexity carrier frequency offset (CFO) estimation and compensation in multi-user massive multiple-input multiple-output (MIMO) systems is a challenging problem. The existing CFO estimation algorithms incur tremendous increase in complexity with increasing number of base station (BS) antennas,

Constant-Envelope Precoding With Time-Variation Constraint on the Transmitted Phase Angles

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Impact of CFO Estimation on the Performance of ZF Receiver in Massive MU-MIMO Systems

and number of user terminals (UTs)

Constant Envelope Pilot-Based Low-Complexity CFO Estimation in Massive MU-MIMO Systems

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Energy-spectral efficiency trade-off for a massive SU-MIMO system with transceiver power consumption

(i.e. massive MIMO regime). In this paper, we address this problem by proposing a novel low-complexity algorithm for CFO estimation which uses the pilot signal received at the BS during special uplink slots. The total per-channel use complexity of the proposed algorithm increases only linearly with increasing

Impact of Frequency Selectivity on the Information Rate Performance of CFO Impaired Single-Carrier Massive MU-MIMO Uplink

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On the Energy-Spectral Efficiency Trade-off of the MRC Receiver in Massive MIMO Systems with Transceiver Power Consumption.

and is independent of

How Much Bandpass Filtering is Required in Massive MIMO Base Stations

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Impact of Underlaid Multi-antenna D2D on Cellular Downlink Users in Massive MIMO Systems.

. Analysis reveals that the CFO estimation accuracy can be considerably improved by increasing

Timing Advance Estimation and Beamforming of Random Access Response in Crowded TDD Massive MIMO Systems.

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