Remote Interference Mitigation through Null Precoding and Fractional Programming

2025-10-10

AI Summary

In 5G systems, atmospheric ducting induces remote interference (RI), where downlink signals from distant base stations propagate beyond the line-of-sight via tropospheric ducts, severely degrading local uplink channel estimation and reception performance. To address this, we propose a transceiver design jointly leveraging angle-of-arrival (AoA) estimation, null-steering precoding, and fractional programming. Our key innovation lies in incorporating physical-layer spatial information—specifically AoA—into the fractional programming framework, enabling precise placement of interference-channel nulls while simultaneously optimizing power efficiency. Experimental results demonstrate a 5.23 dB reduction in normalized mean-square error of uplink channel estimation. Moreover, under previously infeasible low uplink transmit power conditions, the achievable uplink rate improves to approximately 5.8 bit/s/Hz, effectively restoring reliable communication for weak uplink signals.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Distributed Search
• Intelligent Robots: State Estimation

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Search and Retrieval-Augmented AI: Vertical and domain-specific search
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

With the rapid deployment of 5G systems, remote interference (RI) caused by atmospheric ducting has emerged as an occasional, but critical challenge. This phenomenon occurs when the downlink (DL) signals from distant base stations (BSs) propagate over long distances through tropospheric ducting, severely disrupting uplink (UL) reception at local BSs. To address this challenge, we analyze the effect of RI on network performance, including the channel estimation phase. We then develop a solution that identifies the angle-of-arrival (AOA) estimation of RI and designs precoders and combiners that mitigate RI. Our approach employs interference cancellation techniques through null precoding and fractional programming which enhance the performance of the network. Interestingly, we show that using our scheme, uplink communication is possible at low transmit power regimes that were unusable due to RI. Our results further show a 5.23~dB reduction in normalized mean square error for channel estimation and achieved data rates around 5.8~bit/s/Hz at the previously unusable low uplink transmit power conditions.

Problem

• Mitigating remote interference in 5G networks caused by atmospheric ducting
• Developing precoders and combiners through null precoding and fractional programming
• Enabling uplink communication at low transmit power regimes previously unusable

Innovation

• Uses null precoding for interference cancellation
• Applies fractional programming to enhance performance
• Identifies angle-of-arrival estimation of interference