Design of a Digital Signal Processing-Based Noise Cancellation System for Radio Communication in Urban Environments in Abuja

Background: Electromagnetic noise from dense urban infrastructure degrades radio communication quality in Abuja, Federal Capital Territory, affecting emergency service and broadcast communications. Digital signal processing noise cancellation offers effective, adaptive interference reduction. Aim: This study designed and evaluated a DSP-based adaptive noise cancellation system for urban radio communication improvement in Abuja. Methods: A least mean squares adaptive filter algorithm was implemented on a Texas Instruments TMS320C6713 DSP board. The system used a reference antenna to capture ambient noise and an adaptive filter to subtract the noise estimate from the received signal. Performance was evaluated using signal-to-noise ratio improvement and bit error rate reduction at 88 MHz FM and 460 MHz UHF frequencies in field tests at five Abuja locations. Results: SNR improvement averaged 14.3 dB across test locations at 460 MHz. Bit error rate decreased by 78% compared with the unfiltered receiver. Convergence time of the LMS filter was under 50 milliseconds. Conclusion: The DSP-based adaptive noise canceller effectively improves urban radio communication quality. The system is applicable to emergency services, broadcast monitoring, and military communication applications in Nigerian urban environments. Keywords: digital signal processing, noise cancellation, adaptive filter, radio communication, Abuja.