Asynchronous Interference Cancellations for Energy-Efficient Clustering in Ultra-Densely Cellular Networks

IEEE Internet of Things Journal(2024)

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Ultra-dense networks (UDNs) are considered to be a key technology that can meet the growing rate requirements caused by the explosion of user equipments (UEs) in the Internet of Things (IoT) applications. The dense deployment of small-cell base stations (SBSs) facilitates the reuse of spectrum resources but also leads to significant interference among adjacent SBSs. Joint transmission (JT) technology can alleviate inter-cell interference and improve throughput. However, signal processing and backhaul during BS cooperation require additional power consumption, which reduces the energy efficiency (EE) of UDNs. Additionally, the arrival time of received signals from different cooperative BSs at user equipments (UEs) results in asynchronous interference, which poses a significant challenge for JT. To improve EE, we need to determine the clustering strategy and address the interference issue of asynchronous JT. Specifically, the energy-efficiency-centric (EEC) clustering scheme was proposed based on the maximal independent set of graph theory to determine the SBS clusters. In each cluster, asynchronous gap generation and gap compensation operations were employed to eliminate tail interference of asynchronous JT and compensate for the gap between adjacent received blocks, respectively. This approach effectively mitigated the asynchronous interference at UEs. Simulation results demonstrated that the proposed asynchronous interference cancellations in EEC clusters can significantly improve sum rate and EE compared to other schemes.
Energy efficiency,joint transmission,asynchronous interference,clustering
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