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Barry G. Evans

Researcher at University of Surrey

Publications -  497
Citations -  6599

Barry G. Evans is an academic researcher from University of Surrey. The author has contributed to research in topics: Communications satellite & Communication channel. The author has an hindex of 34, co-authored 495 publications receiving 6039 citations. Previous affiliations of Barry G. Evans include University of Essex.

Papers
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Proceedings ArticleDOI

Database-augmented spectrum sensing algorithm for cognitive radio

TL;DR: A novel database-augmented spectrum sensing algorithm is proposed for a secondary access to the TV White Space (TVWS) spectrum that demonstrates a better spectrum efficiency for SUs, and better protection for incumbent PUs than the exiting stand-alone geo-location database model.
Proceedings ArticleDOI

Connection admission control strategy and routing considerations in multimedia (non-geo) satellite networks

TL;DR: The results show that the proposed method for admission control and radio resource management in a multispot-beam satellite network can be implemented in a distributed way that take the user mobility in addition to the service specific parameters in account.
Journal ArticleDOI

Modified sum-product algorithms for decoding low-density parity-check codes

TL;DR: The authors deal with the sum-product algorithm (SPA) based on the hyperbolic tangent (tanh) rule when it is applied for decoding low-density parity-check (LDPC) codes and two novel modifications of the tanh function (and its inverse) are proposed.
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Narrowband channel statistics from multiband propagation measurements applicable to high elevation angle land-mobile satellite systems

TL;DR: The overall analysis of the propagation data indicates that the fading character of the LMS channel is significantly dependent on the surrounding environment, especially at higher path elevation angles.
Journal ArticleDOI

Semi-Adaptive Beamforming for OFDM Based Hybrid Terrestrial-Satellite Mobile System

TL;DR: The proposed algorithm is a dual form of beamforming that enables adaptive and non-adaptive processing to coexist via a robust gradient based switching mechanism and consumes up to 98% less filter computing power as compared to full- Adaptive case without compromising on system performance.