AI-Driven FBMC-OQAM Signal Recognition via Transform Channel Convolution Strategy

With the advent of the Industry 5.0 era,the Internet of Things(IoT)devices face unprecedented proliferation,requiring higher communications rates and lower transmission delays.Considering its high spectrum efficiency,the promising filter bank multicarrier(FBMC)technique using offset quadrature amplitude modulation(OQAM)has been applied to Beyond 5G(B5G)industry IoT networks.However,due to the broadcasting nature of wireless channels,the FBMC-OQAMindustry IoT network is inevitably vulnerable to adversary attacks frommalicious IoT nodes.The FBMC-OQAMindustry cognitive radio network(ICRNet)is proposed to ensure security at the physical layer to tackle the above challenge.As a pivotal step of ICRNet,blind modulation recognition(BMR)can detect and recognize the modulation type of malicious signals.The previous works need to accomplish the BMR task of FBMC-OQAM signals in ICRNet nodes.A novel FBMC BMR algorithm is proposed with the transform channel convolution network(TCCNet)rather than a complicated two-dimensional convolution.Firstly,this is achieved by designing a low-complexity binary constellation diagram(BCD)gridding matrix as the input of TCCNet.Then,a transform channel convolution strategy is developed to convert the image-like BCD matrix into a serieslike data format,accelerating the BMR process while keeping discriminative features.Monte Carlo experimental results demonstrate that the proposed TCCNet obtains a performance gain of 8%and 40%over the traditional inphase/quadrature(I/Q)-based and constellation diagram(CD)-based methods at a signal noise ratio(SNR)of 12 dB,respectively.Moreover,the proposed TCCNet can achieve around 29.682 and 2.356 times faster than existing CD-Alex Network(CD-AlexNet)and I/Q-Convolutional Long Deep Neural Network(I/Q-CLDNN)algorithms,respectively.

Automatic modulation classification using modulation fingerprint extraction

An automatic method for classifying frequency shift keying(FSK),minimum shift keying(MSK),phase shift keying(PSK),quadrature amplitude modulation(QAM),and orthogonal frequency division multiplexing(OFDM)is proposed by simultaneously using normality test,spectral analysis,and geometrical characteristics of in-phase-quadrature(I-Q)constellation diagram.Since the extracted features are unique for each modulation,they can be considered as a fingerprint of each modulation.We show that the proposed algorithm outperforms the previously published methods in terms of signal-to-noise ratio(SNR)and success rate.For example,the success rate of the proposed method for 64-QAM modulation at SNR=11 dB is 99%.Another advantage of the proposed method is its wide SNR range;such that the probability of classification for 16-QAM at SNR=3 dB is almost 1.The proposed method also provides a database for geometrical features of I-Q constellation diagram.By comparing and correlating the data of the provided database with the estimated I-Q diagram of the received signal,the processing gain of 4 dB is obtained.Whatever can be mentioned about the preference of the proposed algorithm are low complexity,low SNR,wide range of modulation set,and enhanced recognition at higher-order modulations.

A 16PSK-OFDM-FSO Communication System under Complex Weather Conditions

Free Space Optical (FSO) communication is one of the most promising access methods. But, the different weather conditions will affect the transceiver performance. In this paper, we build a FSO communication system with 16-ary phase shift key-orthogonal frequency division multiplexing (16PSK-OFDM) downstream signals. We analyze the transmission performance of 16PSK-OFDM optical signals under five different weather conditions (sunny, light rain, moderate rain, snow, and fog). The optical spectral diagrams, constellation diagrams, and bit error rate (BER) of the received signals are simulation measured and analyzed. The results show that the constellation diagram under sunny condition is clear, and the value of BER is about 10?4.2 after 16PSK-OFDM optical signals pass through 500 m FSO link. Note that, the constellation points are dispersed under the other weather conditions.

Secure transmission technology based on direct modulation with random channel characteristics

Aiming at the problem of insufficient security in the existing wireless data trans-mission,a security transmission technology based on direct modulation with random channel characteristics is proposed.The method first estimates channel characteristics using the preamble in the communication frame,and then embeds channel characteristics into the I/Q modulator.After that,the modulated constellation diagram undergoes random hopping of the constellation position compared with the original constellation diagram,thus achieving the effect of secure transmission.Due to the reciprocity of the uplink and downlink channels,channel characteristics estimated by the downlink receiver are almost the same as those esti-mated by the uplink receiver,and the correct plaintext data can be recovered by performing corresponding demodulation with them.Compared with the existing scheme of quantizing channel characteristics and then encrypting data,the method reduces the performance loss caused by quantization.In addition,its bit error rate is lower than that of the quantization method.In general,it has higher security and convenience.

Secure transmission technology based on direct modulation with random channel characteristics

Aiming at the problem of insucient security in the existing wireless data trans-mission,a security transmission technology based on direct modulation with random channel characteristics is proposed.The method rst estimates channel characteristics using the preamble in the communication frame,and then embeds channel characteristics into the I/Q modulator.After that,the modulated constellation diagram undergoes random hopping of the constellation position compared with the original constellation diagram,thus achieving the e ect of secure transmission.Due to the reciprocity of the uplink and downlink channels,channel characteristics estimated by the downlink receiver are almost the same as those esti-mated by the uplink receiver,and the correct plaintext data can be recovered by performing corresponding demodulation with them.Compared with the existing scheme of quantizing channel characteristics and then encrypting data,the method reduces the performance loss caused by quantization.In addition,its bit error rate is lower than that of the quantization method.In general,it has higher security and convenience.