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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In this paper, we consider a network in which lower power nodes (LPNs) are deployed jointly within macrocells. However, there are significant differences between the transmit power levels, coverage areas, and deployment densities of these two types of base stations. Such disparities lead to an unfair load distribution, as well as a lower throughput for picocells'users equipments (UEs). A good solution to such issues is the exploitation of the cell range expansion (CRE) technique. Although CRE has widely proven its effectiveness, it may degrade the network capacity if the cell bias is not chosen properly. In fact, it may generate severe intercell interference at extended region cell (ERC) UEs, which leads to a deterioration of their throughput. We thus propose a downlink coordinated cell range expansion for mobility management (CCREMM) strategy that analytically computes the joint optimal bias at picocells and macrocells. CCREMM mitigates the interference at ERC-UEs by accounting for their maximum tolerable interference. Moreover, CCREMM reaches the load balancing and the UE QoS satisfaction by accounting for additional parameters. It will be proven that our strategy which is associated with the maximum throughput scheduling technique, results in a cell load-balancing improvement, fairness, and a 50-90% UE throughput enhancement. These performance figures are shown to surpass those achieved by alternative approaches proposed in the existing literature.

Optimum Biasing for Cell Load Balancing Under QoS and Interference Management in HetNets