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Found 15 papers, 1 papers with code
Unknown Interference Modeling for Rate Adaptation in Cell-Free Massive MIMO Networks
Co-channel interference poses a challenge in any wireless communication network where the time-frequency resources are reused over different geographical areas.
Power Allocation Scheme for Device-Free Localization in 6G ISAC Networks
Integrated Sensing and Communication (ISAC) is considered one of the crucial technologies in the upcoming sixth-generation (6G) mobile communication systems that could facilitate ultra-precise positioning of passive and active targets and extremely high data rates through spectrum coexistence and hardware sharing.
Cooperative Multi-Monostatic Sensing for Object Localization in 6G Networks
Enabling passive sensing of the environment using cellular base stations (BSs) will be one of the disruptive features of the sixth-generation (6G) networks.
Modeling and Performance Analysis of CSMA-Based JCAS Networks
When sensing and communication share the same spectrum, the communication links in the JCAS networks experience interference from both sensing and communication signals.
Communication-Efficient Orchestrations for URLLC Service via Hierarchical Reinforcement Learning
However, with conventional RL methods, the decision variables (though being deployed at various network layers) are typically optimized in the same control loop, leading to significant practical limitations on the control loop's delay as well as excessive signaling and energy consumption.
Hierarchical Reinforcement Learning
reinforcement-learning
+1
A Bayesian Approach to Characterize Unknown Interference Power in Wireless Networks
The existence of unknown interference is a prevalent problem in wireless communication networks.
Reinforcement Learning-based Joint Handover and Beam Tracking in Millimeter-wave Networks
In this paper, we develop an algorithm for joint handover and beam tracking in millimeter-wave (mmWave) networks.
Device Selection for the Coexistence of URLLC and Distributed Learning Services
Our simulation results confirm that our solution can significantly decrease the training delay of the distributed AI service while keeping the URLLC availability above its required threshold and close to the scenario where URLLC solely consumes all network resources.
Soft Handover Procedures in mmWave Cell-Free Massive MIMO Networks
The algorithms provide a systematic procedure for initial access and update of the serving APs and assigned pilot sequence to each UE.
Location-Aided Beamforming in Mobile Millimeter-Wave Networks
Nevertheless, the need for beamforming and directional communication between the transmitter and the receiver increases the complexity of the channel estimation and link establishment phase.
Learning-Based Downlink Power Allocation in Cell-Free Massive MIMO Systems
Further, we develop a clustered DNN model where the LSF parameters of a small number of APs, forming a cluster within a relatively large network, are used to jointly approximate the power coefficients of the cluster.
Learning-based Load Balancing Handover in Mobile Millimeter Wave Networks
Millimeter-wave (mmWave) communication is a promising solution to the high data rate demands in the upcoming 5G and beyond communication networks.
Learning-based Handover in Mobile Millimeter-wave Networks
We show that our method provides high rate and reliability in all locations of the user's trajectory with a minimal number of handovers.
Efficient Beamforming for Mobile mmWave Networks
We design a lightweight beam-searching algorithm for mobile millimeter-wave systems.
Channel Selection Algorithm for Cognitive Radio Networks with Heavy-Tailed Idle Times
We implement our proposed CSA framework in a wireless test-bed and comprehensively evaluate its performance by recreating the realistic PU channel occupancy patterns.
