2021
DOI: 10.1002/dac.5059
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Exploring the alternatives to the conventional interference mitigation schemes for 5G wireless cellular communication network

Abstract: Summary The manifold increase in the number of cellular wireless network consumers has presented a monumental challenge to upgrade the current infrastructure for imparting superior throughput and good quality of service. End‐users of the network will want super high‐speed data with very low latency, as well as secure and with a lower packet data drop rate. Joint coordination between various network resources such as that of a dense heterogeneous network is crucial for achieving the above demands. It is also in… Show more

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Cited by 4 publications
(3 citation statements)
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“…Table 3 summarizes the recent research contributions, challenges, and future insights on interference mitigation in 5G UAV-assisted wireless networks. It's worth mentioning here that some researchers have proposed alternative methods to the conventional interference mitigation schemes for 5G wireless networks [94]. These methods are shown in Figure 8.…”
Section: Rfa and Decoupled Associationmentioning
confidence: 99%
“…Table 3 summarizes the recent research contributions, challenges, and future insights on interference mitigation in 5G UAV-assisted wireless networks. It's worth mentioning here that some researchers have proposed alternative methods to the conventional interference mitigation schemes for 5G wireless networks [94]. These methods are shown in Figure 8.…”
Section: Rfa and Decoupled Associationmentioning
confidence: 99%
“…The rapid progress in communication is driven by the increasing number of users demanding high-speed data services, necessitating expanded bandwidth [1]. However, wireless communication faces challenges like Inter-Symbol Interference (ISI) and Multi-User Interference (MUI), particularly in high-density user environments [2], [3].…”
Section: Introductionmentioning
confidence: 99%
“…In (21) showed Game Theory (GT) model is very efficient in comparison with machine learning models (22) for obtaining optimal resource allocation in the heterogeneous wireless network. However, existing GT-based resource allocation model (23,24) fail to provide good access fairness (1) with high performance efficiency (2,3) .…”
Section: Introductionmentioning
confidence: 99%