Advanced MIMO Systems Optimization
430 papers on this topic
Residual Cross-Attention Transformer-Based Multi-User CSI Feedback with Deep Joint Source-Channel Coding
This letter proposes a deep-learning (DL)-based multi-user channel state information (CSI) feedback framework for massive multiple-input multiple-output systems, where the deep joint...
OpenRANet: Neuralized Spectrum Access by Joint Subcarrier and Power Allocation with Optimization-based Deep Learning
The next-generation radio access network (RAN), known as Open RAN, is poised to feature an AI-native interface for wireless cellular networks, including emerging satellite-terrestrial systems,...
A Semi-amortized Lifted Learning-to-Optimize Masked (SALLO-M) Transformer Model for Scalable and Generalizable Beamforming
We develop an unsupervised deep learning framework for real-time scalable and generalizable downlink beamforming in multi-user multiple-input single-output (MU-MISO) systems. The proposed...
CLNet: Complex Input Lightweight Neural Network designed for Massive MIMO CSI Feedback
Unleashing the full potential of massive MIMO in FDD mode by reducing the overhead of CSI feedback has recently garnered attention. Numerous deep learning for massive MIMO CSI feedback approaches...
Hierarchical Federated Learning Across Heterogeneous Cellular Networks
We study collaborative machine learning (ML) across wireless devices, each with its own local dataset. Offloading these datasets to a cloud or an edge server to implement powerful ML solutions is...
Rate-Splitting Multiple Access for Multigroup Multicast and Multibeam Satellite Systems
This work focuses on the promising Rate-Splitting Multiple Access (RSMA) and its beamforming design problem to achieve max-min fairness (MMF) among multiple co-channel multicast groups with...
Binarized Aggregated Network with Quantization: Flexible Deep Learning Deployment for CSI Feedback in Massive MIMO System
Massive multiple-input multiple-output (MIMO) is one of the key techniques to achieve better spectrum and energy efficiency in 5G system. The channel state information (CSI) needs to be fed back...
Channel Estimation for Extremely Large-Scale Massive MIMO Systems
Extremely large-scale massive multiple-input multiple-output (MIMO) has shown considerable potential in future mobile communications. However, the use of extremely large aperture arrays has led to...
Rate-Splitting Unifying SDMA, OMA, NOMA, and Multicasting in MISO Broadcast Channel: A Simple Two-User Rate Analysis
Considering a two-user multi-antenna Broadcast Channel, this paper shows that linearly precoded Rate-Splitting (RS) with Successive Interference Cancellation (SIC) receivers is a flexible...
GBLinks: GNN-Based Beam Selection and Link Activation for Ultra-dense D2D mmWave Networks
In this paper, we consider the problem of joint beam selection and link activation across a set of communication pairs to effectively control the interference between communication pairs via...
Machine Learning-Enabled Joint Antenna Selection and Precoding Design: From Offline Complexity to Online Performance
We investigate the performance of multi-user multiple-antenna downlink systems in which a BS serves multiple users via a shared wireless medium. In order to fully exploit the spatial diversity...
Heterogenous Networks: From small cells to 5G NR-U
With the exponential increase in mobile users, the mobile data demand has grown tremendously. To meet these demands, cellular operators are constantly innovating to enhance the capacity of...
Enhancing Deep Learning Performance of Massive MIMO CSI Feedback
CSI feedback is an important problem of Massive multiple-input multiple-output (MIMO) technology because the feedback overhead is proportional to the number of sub-channels and the number of...
Modulation Compression in Next Generation RAN: Air Interface and Fronthaul trade-offs
Modulation compression is a technique considered in the recent Open-RAN (O-RAN) framework, which has continued the 3GPP effort towards the definition of new virtualized and multi-vendor RAN...
Pencil Beamforming Increases Human Exposure to ElectroMagnetic Fields: True or False?
According to a very popular belief - very widespread among non-scientific communities - the exploitation of narrow beams, a.k.a. "pencil beamforming", results in a prompt increase of exposure...
Graph Embedding based Wireless Link Scheduling with Few Training Samples
Link scheduling in device-to-device (D2D) networks is usually formulated as a non-convex combinatorial problem, which is generally NP-hard and difficult to get the optimal solution. Traditional...
Joint Power Control and LSFD for Wireless-Powered Cell-Free Massive MIMO
This paper considers wireless uplink information and downlink power transfer in cell-free massive multiple-input multiple-output systems. The single-antenna user equipments (UEs) utilize the...
On the Performance Gain of NOMA over OMA in Uplink Communication Systems
In this paper, we investigate and reveal the ergodic sum-rate gain (ESG) of non-orthogonal multiple access (NOMA) over orthogonal multiple access (OMA) in uplink cellular communication systems. A...