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
base station (BS) serves multiple users via a shared wireless medium. In order to fully …
base station (BS) serves multiple users via a shared wireless medium. In order to fully …
A survey of low-energy parallel scheduling algorithms
High energy consumption is one of the biggest obstacles to the rapid development of
computing systems, and reducing energy consumption is quite urgent and necessary for …
computing systems, and reducing energy consumption is quite urgent and necessary for …
Data-driven relay selection for physical-layer security: A decision tree approach
X Wang, F Liu - IEEE Access, 2020 - ieeexplore.ieee.org
Conventional optimization-driven secure relay selection relies on maximization algorithm
and accurate channel state information (CSI) of both legitimate and eavesdropper channels …
and accurate channel state information (CSI) of both legitimate and eavesdropper channels …
Learning-assisted optimization for energy-efficient scheduling in deadline-aware NOMA systems
In this paper, we study a class of minimum-energy scheduling problems in non-orthogonal
multiple access (NOMA) systems. NOMA is adopted to enable efficient channel utilization …
multiple access (NOMA) systems. NOMA is adopted to enable efficient channel utilization …
Dynamic bandwidth allocation and precoding design for highly-loaded multiuser MISO in beyond 5G networks
Multiuser techniques play a central role in the fifth-generation (5G) and beyond 5G (B5G)
wireless networks that exploit spatial diversity to serve multiple users simultaneously in the …
wireless networks that exploit spatial diversity to serve multiple users simultaneously in the …
Learning-based resource allocation: Efficient content delivery enabled by convolutional neural network
In practical content delivery, when the time-frequency resources are limited, it is a
challenging task to satisfy terminals' data demand in a heavy-traffic and mutual-interfered …
challenging task to satisfy terminals' data demand in a heavy-traffic and mutual-interfered …
Machine learning based antenna selection and power allocation in multi-user MISO systems
We investigate the performance of multi-user multiple-antenna downlinks via joint antenna
selection and power control design. In order to fully exploit the spatial diversity while …
selection and power control design. In order to fully exploit the spatial diversity while …
[HTML][HTML] Machine learning-based relay selection for secure transmission in multi-hop DF relay networks
A relay selection method is proposed for physical-layer security in multi-hop decode-and-
forward (DF) relaying systems. In the proposed method, cooperative relays are selected to …
forward (DF) relaying systems. In the proposed method, cooperative relays are selected to …
Deep learning based user grouping for FD-MIMO systems exploiting statistical channel state information
The joint spatial division and multiplexing (JSDM) is a two-phase precoding scheme for
massive multiple-input-multiple-output (MIMO) system under frequency division duplex …
massive multiple-input-multiple-output (MIMO) system under frequency division duplex …
Machine learning integration in Communication system for efficient selection of signals
Through combined antenna selecting and power management design, we examine the
effectiveness of multi-user multiple-antenna downlinks. A fraction of antennas are chosen to …
effectiveness of multi-user multiple-antenna downlinks. A fraction of antennas are chosen to …