most citedDistributed Massive MIMO Channel Estimation and Channel Database Assistance

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SP2019

A Low Complexity Near-Maximum Likelihood MIMO Receiver with Low Resolution Analog-to-Digital Converters

Arkady Molev-Shteiman, Xiao-Feng Qi, Laurence Mailaender

Based on a new equivalent model of quantizer with noisy input recently presented in [23], we propose a new low complexity receiver that takes into account the nonlinear distortion…

eess.SP2019

Low Resolution Digital-to-Analog Converter with Digital Dithering for MIMO Transmitter

Arkady Molev-Shteiman, Xiao-Feng Qi, Laurence Mailaender

Based on an equivalent model for quantizers with noisy inputs recently presented in [35], we propose a method of digital dithering at the transmitter that may significantly reduce…

cs.NI20191 cited

New equivalent model of quantizer with noisy input and its application for ADC resolution determination in an uplink MIMO receiver

Arkady Molev-Shteiman, Xiao-Feng Qi, Laurence Mailaender +2

When a quantizer input signal is the sum of the desired signal and input white noise, the quantization error is a function of total input signal. Our new equivalent model splits th…

cs.IT20172 cited

Distributed Massive MIMO Channel Estimation and Channel Database Assistance

Arkady Molev-Shteiman, Laurence Mailaender, Xiao-Feng Qi

Due to the low per-antenna SNR and high signaling overhead, channel estimation is a major bottleneck in Massive MIMO systems. Spatial constraints can improve estimation performance…

cs.IT2017

Direct Positioning with Channel Database Assistance

Laurence Mailaender, Arkady Molev-Shteiman, Xiao-Feng Qi

When we have knowledge of the positions of nearby walls and buildings, estimating the source location becomes a very efficient way of characterizing and estimating a radio channel.…