On generalized eigenvector space for target detection in reduced dimensions

Güvensen, Gökhan M.; Candan, Çağatay; Koc, Sencer; Orguner, Umut

doi:10.1109/radar.2015.7131199

Cited by 7 publications

(9 citation statements)

References 13 publications

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“…Similarity transformation does not affect the cost function since generalized eigenvectors diagonalize this term [44]. Hence, alternative representations of GEB can be used without loss of performance.…”

Section: Appendix C Proof Of Lemmamentioning

confidence: 99%

An Efficient Interference-Aware Constrained Massive MIMO Beamforming for mm-Wave JSDM

Bayraktar

Güvensen

2021

IEEE Access

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Low-complexity beamformer design with practical constraints is an attractive research area for hybrid analog/digital systems in mm-wave massive multiple-input multiple-output (MIMO). This paper investigates interference-aware pre-beamformer (analog beamformer) design for joint spatial division and multiplexing (JSDM) which is a user-grouping based two-stage beamforming method. Single-carrier frequency domain equalization (SC-FDE) is employed in uplink frequency-selective channels. First, unconstrained slowly changing statistical analog beamformer of each group, namely, generalized eigenbeamformer (GEB) which has strong interference suppression capability is designed by maximizing the mutual information in reduced dimension. Then, constant-modulus constrained approximations of unconstrained beamformer are obtained by utilizing alternating minimization algorithms for fully connected arrays and fixed subarrays. In addition, a dynamic subarray algorithm is proposed where the connections between radio frequency (RF) chains and antennas are changed with changing channel statistics. Convergence of the proposed alternating minimization-based algorithms are provided along with their complexity analysis. It is observed that additional complexity of proposed algorithms is insignificant for the overall system design. Although most of the interference is suppressed with the help of proposed constrained beamformers, there may be some residual interference after analog beamforming stage. Thus, minimum mean square error (MMSE) criterion based iterative block decision feedback equalization (IB-DFE) method, which takes the residual interference in reduced dimension into account, is promoted for digital beamforming stage. Simulation results verify the superiority of the proposed interference-aware constrained design over existing approaches in terms of beampattern, spectral efficiency, outage capacity, bit-error rate (BER) and channel estimation accuracy.

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Section: Appendix C Proof Of Lemmamentioning

confidence: 99%

An Efficient Interference-Aware Constrained Massive MIMO Beamforming for mm-Wave JSDM

Bayraktar

Güvensen

2021

IEEE Access

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“…Replacing S (g) with S (g) A results in a similarity transformation for the second term in the determinant in (12), i.e., A −1 [S (g) ] H R (g) η S (g) −1 [S (g) ] H R (g) s S (g) A. Similarity transformation does not affect the cost function since generalized eigenvectors diagonalize this term [41]. Hence, alternative representations of GEB can be used without loss of performance.…”

Section: Appendix B Proof Of Lemmamentioning

confidence: 99%

An Efficient Interference-Aware Constrained Massive MIMO Beamforming for mm-Wave JSDM

Bayraktar¹,

Güvensen²

2021

Preprint

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Low-complexity beamformer design with practical constraints is an attractive research area for hybrid analog/digital systems in mm-wave massive multiple-input multiple-output (MIMO). This paper investigates interference-aware pre-beamformer (analog beamformer) design for joint spatial division and multiplexing (JSDM) which is a user-grouping based two-stage beamforming method. Single-carrier frequency domain equalization (SC-FDE) is employed in uplink frequency-selective channels. First, unconstrained slowly changing statistical analog beamformer of each group, namely, generalized eigenbeamformer (GEB) which has strong interference suppression capability is designed where the mutual information in reduced dimension is maximized. Then, constant-modulus constrained approximations of unconstrained beamformer are obtained by utilizing alternating minimization algorithms for fully connected arrays and fixed subarrays. In addition, a dynamic subarray algorithm is proposed where the connections between radio frequency (RF) chains and antennas are changed with changing channel statistics. Convergence of the proposed alternating minimization-based algorithms are provided along with their complexity analysis. It is observed that additional complexity of proposed algorithms is insignificant for the overall system design. Although most of the interference is suppressed with the help of proposed constrained beamformers, there may be some residual interference after the analog beamforming stage. Therefore, linear minimum mean square error (LMMSE) type digital beamformers, which take the residual interference in reduced dimension into account, are proposed instead of zero-forcing (ZF) type. Simulation results verify the superiority of the proposed interference-aware constrained design over existing approaches in terms of beampattern, spectral efficiency, outage capacity and channel estimation accuracy.

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Section: A Joint Angle-delay Domain Reduced Rank Mmse Estimatormentioning

confidence: 99%

“…Briefly, the D × D positive semi-definite SNR (g) mimo (l) matrix in the spatial domain can be regarded as the generalized definition of the beamformer output snr for general rank signal models [34], [38] 16 . As it was shown in our previous work [38], Tr SNR (6), and the other elements are set to zero. In (22), the SNR (g) mimo (l) matrix is responsible for spatial processing only, utilizing the eigenspaces of the intended group g at l th delay and the inter-group interference after subspace projection onto S In order to harness the spatial multiplexing in each group, one consider the effective multi-path channel vector of each group user h…”

Section: A Joint Angle-delay Domain Reduced Rank Mmse Estimatormentioning

confidence: 99%

“…, L g − 1 have useful properties explained in Appendix I. Briefly, the D × D positive semi-definite SNR (g) mimo (l) matrix in the spatial domain can be regarded as the generalized definition of the beamformer output snr for general rank signal models [34], [38] 16 . As it was shown in our previous work [38], Tr SNR (g) mimo (l) is actually the expected value of the point signal-to-interference noise ratio (sinr) over the eigenspace (AoA support) of the l th MPC in group g, where the point sinr is defined as the output snr after beamforming when the beam is steered towards a point, i.e., angular location in the AoA support of l th MPC.…”

Section: A Joint Angle-delay Domain Reduced Rank Mmse Estimatormentioning

confidence: 99%

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A Generalized Framework on Beamformer Design and CSI Acquisition for Single-Carrier Massive MIMO Systems in Millimeter Wave Channels

Güvensen

Ayanoğlu

2016

2016 IEEE Globecom Workshops (GC Wkshps)

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Recently, a two-stage beamforming concept under the name of Joint Spatial Division and Multiplexing (JSDM), a kind of divide-and-conquer approach based on statistical user-grouping, has been proposed to enable simplified system operations in massive MIMO. In this study, we establish a general framework on the reduced dimensional channel state information (CSI) estimation and pre-beamformer design for frequency-selective massive MIMO systems employing single-carrier (SC) modulation in time division duplex (TDD) mode by exploiting the joint angle-delay domain channel sparsity in millimeter (mm) wave frequencies (which is often characterized with limited scattering and hence correlatedness in the spatial domain). The main contribution of this work is threefold. First, by an inspiration from the user-grouping idea (in the JSDM framework), the reduced rank minimum mean square error (RR-MMSE) instantaneous CSI estimator, based on generic subspace projection taking the joint angle-delay power profile into account, is derived for spatially correlated wideband MIMO channels. Second, the statistical prebeamformer design is considered for frequency-selective SC massive MIMO channels. We examine the dimension reduction and subspace (beamspace) construction on which the RR-MMSE estimation can be realized as accurately as possible. The generalized eigenvector beamspace (GEB) appears to be a nearly optimal pre-beamformer when the eigenspaces of different resolvable multi-path components are assumed to be nearly orthogonal. Finally, a spatio-temporal domain correlator type reduced rank channel estimator, as an approximation of the RR-MMSE estimate, is obtained by carrying out least square (LS) estimation in a proper reduced dimensional beamspace. It is observed that the proposed techniques show remarkable robustness to the pilot interference (or contamination) with a significant reduction in pilot overhead thanks to the subspace projection. Index TermsThe authors are with the Center for Pervasive Communications and Computing (CPCC),

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On generalized eigenvector space for target detection in reduced dimensions

Cited by 7 publications

References 13 publications

An Efficient Interference-Aware Constrained Massive MIMO Beamforming for mm-Wave JSDM

An Efficient Interference-Aware Constrained Massive MIMO Beamforming for mm-Wave JSDM

An Efficient Interference-Aware Constrained Massive MIMO Beamforming for mm-Wave JSDM

A Generalized Framework on Beamformer Design and CSI Acquisition for Single-Carrier Massive MIMO Systems in Millimeter Wave Channels

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