Space-Time Block Coding Based Beamforming for Beam Squint Compensation
August 30, 2018 Β· Declared Dead Β· π IEEE Wireless Communications Letters
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Ximei Liu, Deli Qiao
arXiv ID
1808.10117
Category
cs.IT: Information Theory
Citations
54
Venue
IEEE Wireless Communications Letters
Last Checked
5 months ago
Abstract
In this paper, the beam squint problem, which causes significant variations in radiated beam gain over frequencies in millimeter wave communication system, is investigated. A constant modulus beamformer design, which is formulated to maximize the expected average beam gain within the bandwidth with limited variation over frequencies within the bandwidth, is proposed. A semidefinite relaxation (SDR) method is developed to solve the optimization problem under the constant modulus constraints. Depending on the eigenvalues of the optimal solution, either direct beamforming or transmit diversity based beamforming is employed for data transmissions. Through numerical results, the proposed transmission scheme can compensate for beam squint effectively and improve system throughput. Overall, a transmission scheme for beam squint compensation in wideband wireless communication systems is provided.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Information Theory
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems
R.I.P.
π»
Ghosted
Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network
π
π
The Cartographer
Wireless Communications with Unmanned Aerial Vehicles: Opportunities and Challenges
R.I.P.
π»
Ghosted
Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication
π
π
The Cartographer
An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted