# Compressive Wideband Spectrum Sensing Aided Intelligence Transmitter Design

## TL;DR

This paper proposes an intelligent transmitter design that uses wideband sensing to optimize communication in interference-heavy environments.

## Contribution

The novel contribution is a self-interference cancellation architecture based on the Nyquist folding receiver (NYFR) for wideband spectrum sensing.

## Key findings

- The NYFR-based system's interference cancellation performance degrades with time synchronization errors and folding multiples.
- The proposed scheme improves frequency detection probability by about 80% under an SI-to-NCS power ratio of 0 dB.
- The system is highly sensitive to time synchronization errors, which significantly impact cancellation performance.

## Abstract

In order to realize robust communication in complicated interference electromagnetic environments, an intelligent transmitter design is proposed in this paper, where an auxiliary wideband receiver senses the electromagnetic distribution information in a wide bandwidth range to decide the optimal working frequency. One of the key issues is suppressing the self-interference of high-power transmitter signals to the co-platform wideband sensing receiver. Due to the multipath effect of the self-interference channel, perfect time synchronization of self-interference signals is not achievable, which reduces the interference cancelation performance of the co-platform. Therefore, this paper investigates the impact of time synchronization errors on the self-interference cancellation performance of the Nyquist folding receiver (NYFR)-based system. First, a self-interference cancellation architecture based on NYFR is proposed to support the realization of real-time wideband spectrum sensing. Secondly, closed-form expressions for the residual interference power and the self-interference cancellation performance are derived, and the impact of reference signal sampling errors on the self-interference cancellation performance is also analyzed. Theoretical analysis and simulation results show that the NYFR-based self-interference cancellation performance decreases with increasing time synchronization errors and folding multiples, and the system is especially sensitive to time synchronization errors. Moreover, frequency detection simulations show that, under an SI-to-NCS power ratio of 0 dB, the proposed interference cancellation scheme improves the frequency detection probability by approximately 80%. The research results provide a theoretical reference for the compressed sensing-aided intelligent transmitter realization.