Beamspace Aware Adaptive Channel Estimation for Single-Carrier Time-varying Massive MIMO Channels

Download

index.pdf

Date

2017-05-25

Author

Güvensen, Gökhan Muzaffer

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

166
views

80
downloads

In this paper, the problem of sequential beam construction and adaptive channel estimation based on reduced rank (RR) Kalman filtering for frequency-selective massive multipleinput multiple-output (MIMO) systems employing single-carrier (SC) in time division duplex (TDD) mode are considered. In two-stage beamforming, a new algorithm for statistical pre - beamformer design is proposed for spatially correlated timevarying wideband MIMO channels under the assumption that the channel is a stationary Gauss-Markov random process. Th e proposed algorithm yields a nearly optimal pre-beamformer whose beam pattern is designed sequentially with low complexity by taking the user-grouping into account, and exploiting th e properties of Kalman filtering and associated prediction error covariance matrices. The resulting design, based on the second order statistical properties of the channel, generates beamspace on which the RR Kalman estimator can be realized as accuratel y as possible. It is observed that the adaptive channel estimation technique together with the proposed sequential beamspace construction shows remarkable robustness to the pilot interference. This comes with significant reduction in both pilot overhead and dimension of the pre-beamformer lowering both hardware complexity and power consumption.

Subject Keywords

Joint spatial division, Downlink, Systems, Design

URI

https://hdl.handle.net/11511/33135

DOI

https://doi.org/10.1109/icc.2017.7996672

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Reliable Low Resolution 01-4DM Receivers via Deep Learning Balevi, Eren; Andrews, Jeffrey G. (2018-01-01) This paper develops novel deep learning-based architectures and design methodologies for an orthogonal frequency division multiplexing (OFDM) receiver under the constraint of one-bit complex quantization. Single bit quantization greatly reduces complexity and power consumption, but makes accurate data detection difficult. This is particularly true for multicarrier waveforms, which have high peak-to-average ratio in the time domain and fragile subcarrier orthogonality in the frequency domain. The severe dist...
One-Bit OFDM Receivers via Deep Learning Balevi, Eren; Andrews, Jeffrey G. (2019-06-01) This paper develops novel deep learning-based architectures and design methodologies for an orthogonal frequency division multiplexing (OFDM) receiver under the constraint of one-bit complex quantization. Single bit quantization reduces greatly the complexity and power consumption but makes accurate channel estimation and data detection difficult. This is particularly true for multicarrier waveforms that have high peak-to-average power ratio in the time domain and fragile subcarrier orthogonality in the fre...
Beamspace Approach for Detection of the Number of Coherent Sources Candan, Çağatay; Koç, Seyit Sencer (2012-05-11) A beamspace approach is presented to detect the multiplicity of impinging sources on the sensor array for the direction of arrival estimation problem. The method applies to the coherent signals and can also be used to detect the presence of interfering multipath signal. In many applications, the signal to noise ratio is not sufficient to resolve multiple sources with close spatial frequencies. The suggested method is to detect the presence of an interfering secondary source which can not be possibly resolved.
Simple derivative-free nonlinear state observer for sensorless AC drives Akin, Bilal; Orguner, Umut; Ersak, Aydin; Ehsani, Mehrdad (Institute of Electrical and Electronics Engineers (IEEE), 2006-10-01) In this paper, a new Kalman filtering technique, unscented Kalman filter (UKF), is utilized both experimentally and theoretically as a state estimation tool in field-oriented control (FOC) of sensorless ac drives. Using the advantages of this recent derivative-free nonlinear estimation tool, rotor speed and dq-axis fluxes of an induction motor are estimated only with the sensed stator currents and voltages information. In order to compare the estimation performances of the extended Kalman filter (EKF) and U...
SDIVA: Structural Delay Insensitivity Verification Analysis Method for Bit-Level Pipelined Systolic Arrays with Early Output Evaluation Ismailoglu, A. Neshn; Askar, Murat (2008-09-05) A structural delay-insensitivity verification analysis method, SDIVA, is proposed for asynchronous systolic arrays in dual-rail threshold logic style. The SDIVA method employs symbolic delays for all output evaluation paths and works at the behavioral specification level. For bit-level pipelined systolic arrvys, which have data-dependent early output evaluation in one-dimension, SDIVA method reduces the verification analysis task to examination of three adjacent systoles so that by analyzing all possible ea...

Citation Formats

G. M. Güvensen, “Beamspace Aware Adaptive Channel Estimation for Single-Carrier Time-varying Massive MIMO Channels,” 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/33135.