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Efficient modulation classification remains a key challenge in contemporary communication systems research. In this work, we introduce a novel framework rooted in the principle of divide and conquer to address the complexities associated with jointly classifying linear and nonlinear modulation schemes. Our approach decomposes the classification task into multiple binary problems, effectively leveraging a hierarchical tree-based structure that integrates several low-parameterized CNNs. Simulation results validate the efficacy of our proposed method, demonstrating superior classification performance with a notable reduction in complexity compared to conventional single CNN- based approaches.

An orbital angular momentum directional modulation (OAM-DM) signal is proposed for communication and guidance integration. This signal is transmitted by a uniform circular antenna array (UCA). We divide the array into odd and even antenna groups. Each group is excited by differential coded digital modulation waveform to send different signal constellations in different directions. In order to improve the performance of angle estimation, we have designed specific phase shift sequences to obtain the different OAM modes. Mode detection can eliminate multiple value ambiguity of elevation and azimuth angles. The single antenna receiver can demodulate the OAM-DM signal to communicate, detect OAM modes and estimate angles in different directions. Finally, we assess the effectiveness of the proposed approach via numerical simulation.

A method utilizing the cyclic spectral analysis (CSA) and reduced-rank multistage Wiener filtering (RR-MSWF) algorithm to mitigate the interference for the GPS receiver is proposed. In many cases, interference from adjacent channel or from cochannel overlaps on the weak global positioning system (GPS) signal in both time and frequency domains, and it is hard to mitigate this kind of strong interference with the conventional filtering techniques. While with the proposed method given in the paper, we can mitigate the interference effectively. The general process of the proposed method is that first we get the cyclic frequencies (CFs) of the strong interference by CSA of the received GPS signal. And then with the obtained CFs of the interference, we use the blind adaptive frequency shift (BA-FRESH) filter to get the principal process of mitigating the strong interference and separating the weak GPS signal. Finally by utilizing the efficient RR-MSWF algorithm to implement the BA-FRESH filtering, we can mitigate the strong interference effectively and hence improve the performance of the GPS receiver.

An efficient method for GPS multipath mitigation is proposed. The motivation for this proposed method is to integrate the Teager-Kaiser Operator (TKO) with the Multipath Estimating Delay Lock Loop (MEDLL) module to mitigate the GPS multipath efficiently. The general implementation process of the proposed method is that we first utilize the TKO to operate on the received signal’s Auto-Correlation Function (ACF) to get an initial estimate of the multipaths. Then we transfer the initial estimated results to the MEDLL module for a further estimation. Finally, with a few iterations which are less than those of the original MEDLL algorithm, we can get a more accurate estimate of the Line-Of-Sight (LOS) signal, and thus the goal of the GPS multipath mitigation is achieved. The simulation results show that compared to the original MEDLL algorithm, the proposed method can reduce the computation load and the hardware and/or software consumption of the MEDLL module, meanwhile, without decreasing the algorithm accuracy.