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Found 15 papers, 1 papers with code
Channel Estimation for AFDM With Superimposed Pilots
To improve the SE, we propose a novel AFDM channel estimation scheme by introducing the superimposed pilots in the DAFT domain.
Near-Field Channel Estimation in Dual-Band XL-MIMO with Side Information-Assisted Compressed Sensing
Specifically, we formulate the dual-band near-field communication model based on the fact that high-frequency systems are likely to be deployed with lower-frequency systems.
Block-Dominant Compressed Sensing for Near-Field Communications: Fundamentals, Solutions and Future Directions
Near-field (NF) communications draw much attention in the context of extremely large-scale antenna arrays (ELAA).
Wavenumber Domain Sparse Channel Estimation in Holographic MIMO
In this paper, we investigate the sparse channel estimation in holographic multiple-input multiple-output (HMIMO) systems.
Block-Sparse Tensor Recovery
This work explores the fundamental problem of the recoverability of a sparse tensor being reconstructed from its compressed embodiment.
Cross-Domain Dual-Functional OFDM Waveform Design for Accurate Sensing/Positioning
For the communication-centric design, to maximize the achievable data rate, a fraction of REs are optimally allocated for communications according to prior knowledge of the communication channel.
Improving the Performance of R17 Type-II Codebook with Deep Learning
The Type-II codebook in Release 17 (R17) exploits the angular-delay-domain partial reciprocity between uplink and downlink channels to select part of angular-delay-domain ports for measuring and feeding back the downlink channel state information (CSI), where the performance of existing deep learning enhanced CSI feedback methods is limited due to the deficiency of sparse structures.
Deep Learning Empowered Type-II Codebook: New Paradigm for Enhancing CSI Feedback
In contrast to its counterpart in Release 16, the Type-II codebook in Release 17 (R17) exploits the angular-delay-domain partial reciprocity between uplink and downlink channels and selects part of angular-delay-domain ports for measuring and feeding back the downlink CSI, where the performance of the conventional deep learning methods is limited due to the deficiency of sparse structures.
Doppler-Resilient Design of CAZAC Sequences for mmWave/THz Sensing Applications
For an arbitrary-length ZC sequence, a feasible range of the root index is derived to satisfy the requirement of PSLR within the scope of RoI.
Joint Block-Sparse Recovery Using Simultaneous BOMP/BOLS
We consider the greedy algorithms for the joint recovery of high-dimensional sparse signals based on the block multiple measurement vector (BMMV) model in compressed sensing (CS).
Terahertz Wireless Communications with Flexible Index Modulation Aided Pilot Design
Terahertz (THz) wireless communication is envisioned as a promising technology, which is capable of providing ultra-high-rate transmission up to Terabit per second.
Waveform Design for Joint Sensing and Communications in Millimeter-Wave and Low Terahertz Bands
Finally, a data-embedded MS-QP (DE-MS-QP) waveform is constructed through time-domain extension of the MS-QP sequence, generating null frequency points on each subband for data transmission.
Deep Learning Assisted Calibrated Beam Training for Millimeter-Wave Communication Systems
To tackle this problem, the second scheme adopts long-short term memory (LSTM) network for tracking the movement of users and calibrating the beam direction according to the received signals of prior beam training, in order to enhance the robustness to noise.
Deep Learning Assisted mmWave Beam Prediction with Prior Low-frequency Information
Huge overhead of beam training poses a significant challenge to mmWave communications.
NOMA BASED SPATIAL MODULATION
By introducing non-OMA (NOMA) into SM for DL-MU transmission, NOMA-based SM (NOMA-SM) is proposed to mitigate inter-user interference, while maintaining high spectral efficiency.
