OF-FSE: An Efficient Adaptive Equalization for QAM-Based UAV Modulation Systems

Abstract

Quadrature amplitude modulation (QAM) is one of the essential components of unmanned 1 aerial vehicle (UAV) communications. However, the output signal accuracy of QAM deteriorates dramatically and even collapses in the case of UAVs in a harsh channel environment. This is due to the fractionally spaced equalization based on the multi-modulus blind equalization algorithm being implemented prior to carrier synchronization in QAM-based UAV modulation systems. The carrier frequency offset from the harsh channel signal thus contributes to the significantly degraded performance of MMA by suffering the fractionally spaced equalization. Therefore, in this paper, a novel offset feedback fractionally spaced equalization architecture for UAVs to eliminate the carrier frequency offset is first proposed. In this architecture, the carrier frequency offset allows estimated and incorporation into the input signal of fractionally spaced equalization to compensate for the offset. Moreover, a new multi-modulus decision-directed algorithm is presented for the novel architecture to improve the received signal accuracy of UAVs further. It enables adaptive optimization of the convergence process in accordance with the dynamic UAV communication environment employing the multi-modulus blind equalization algorithm and decision-directed blind equalization algorithm (MDD). Simulation results demonstrate the effectiveness of the OF-FSE framework in enabling the QAM-based UAV modulation systems operation in harsh channel scenarios. Moreover, the performance of the presented new MDD algorithm compared with baseline approaches is also confirmed.

Analysis of Adaptive Equalization Algorithms

“…This is mainly because equalization technology is required in the digital communication system, whether through the public switched telephone network, or through the short wave channel, microwave channel or satellite channel to transmit information. Zhang proposed a new multi-modulus and decision-oriented blind equalization algorithm based on the offset feedback fractionally spaced equalization (OF-FSE) framework, which can adaptively adjust the convergence state of various dynamic environments [6]. Wei designed a deep autoencoder network (DAN) and deep learning (DL) model that can be trained with a unified loss function and a unified optimization algorithm to implement various modems [7].…”

OTFS-IM Modulation Based on Four-Dimensional Spherical Code in Air-to-Ground Communication

“…UAVs can have significant influence in agriculture, aerial surveys, and public rescue, and can even be used as a satellite communication relay to expand coverage and ensure communication quality. The drone network has also been developed comprehensively, such as through a novel offset feedback fractionally spaced equalization architecture, the design of drone-aided IoT networking, and a high-mobility support system for NTN connectivity [4][5][6]. In terms of profit, a UAV can be used as a cost-effective air platform for A2G communications.…”