Design Framework of Unsourced Multiple Access for 6G Massive IoT

In this paper,ambient IoT is used as a typical use case of massive connections for the sixth generation(6G)mobile communications where we derive the performance requirements to facilitate the evaluation of technical solutions.A rather complete design of unsourced multiple access is proposed in which two key parts:a compressed sensing module for active user detection,and a sparse interleaver-division multiple access(SIDMA)module are simulated side by side on a same platform at balanced signal to noise ratio(SNR)operating points.With a proper combination of compressed sensing matrix,a convolutional encoder,receiver algorithms,the simulated performance results appear superior to the state-of-the-art benchmark,yet with relatively less complicated processing.

High-speed GaN-based laser diode with modulation bandwidth exceeding 5 GHz for 20 Gbps visible light communication

Visible light communication(VLC)based on laser diodes demonstrates great potential for high data rate maritime,terrestrial,and aerial wireless data links.Here,we design and fabricate high-speed blue laser diodes(LDs)grown on c-plane gallium nitride(GaN)substrate.This was achieved through active region design and miniaturization toward a narrow ridge waveguide,short cavity length,and single longitudinal mode Fabry–Perot laser diode.The fabricated mini-LD has a low threshold current of 31 mA and slope efficiency of 1.02 W/A.A record modulation bandwidth of 5.9 GHz(−3dB)was measured from the mini-LD.Using the developed mini-LD as a transmitter,the VLC link exhibits a high data transmission rate of 20.06 Gbps adopting the bit and power loading discrete multitone(DMT)modulation technique.The corresponding bit error rate is 0.003,satisfying the forward error correction standard.The demonstrated GaN-based mini-LD has significantly enhanced data transmission rates,paving the path for energy-efficient VLC systems and integrated photonics in the visible regime.

Model division multiple access for semantic communications

In a multi-user system,system resources should be allocated to different users.In traditional communication systems,system resources generally include time,frequency,space,and power,so multiple access technologies such as time division multiple access(TDMA),frequency division multiple access(FDMA),space division multiple access(SDMA),code division multiple access(CDMA),and non-orthogonal multiple access(NOMA)are widely used.In semantic communication,which is considered a new paradigm of the next-generation communication system,we extract high-dimensional features from signal sources in a model-based artificial intelligence approach from a semantic perspective and construct a model information space for signal sources and channel features.From the high-dimensional semantic space,we excavate the shared and personalized information of semantic information and propose a novel multiple access technology,named model division multiple access(MDMA),which is based on the resource of the semantic domain.From the perspective of information theory,we prove that MDMA can attain more performance gains than traditional multiple access technologies.Simulation results show that MDMA saves more bandwidth resources than traditional multiple access technologies,and that MDMA has at least a 5-dB advantage over NOMA in the additive white Gaussian noise(AWGN)channel under the low signal-to-noise(SNR)condition.