English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Hybrid analog and digital (HAD) beamforming has been recently receivingconsiderable deserved attention for a practical implementation on thelarge-scale antenna systems. As compared to full digital beamforming,partial-connected HAD beamforming can significantly reduce the hardware cost,complexity, and power consumption. In this paper, in order to mitigate thejamming along with lowering the hardware complexity and cost by reducing thenumber of RF chains needed, a novel hybrid analog and digital receivebeamformer based on an improved bat algorithm (I-BA) and the phase-only isproposed. Our proposed beamformer is compared with robust adaptive beamformers(RABs) methods proposed by us, which are considered in the digital beamformingpart. The evolutionary optimization algorithm is proposed since most of the RABmethods are sensitive to the DOA mismatch, and depending on the complexweights, resulting in an expensive receiver. In the analog part, analog phasealignment by linear searching (APALS) with a sufficiently fine grid of pointsis employed to optimize the analog beamformer matrix. The performance of theproposed I-BA is revealed using MATLAB simulation and compared with BA, andParticle swarm optimization (PSO) algorithms, which shows a better performancein terms of convergence speed, stability, and the ability to jump from thelocal minima.

An Efficient Hybrid Beamforming Design for Massive MIMO Receive Systems via SINR Maximization Based on an Improved Bat Algorithm