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Found 17 papers, 2 papers with code
Learning to Optimize Resource Assignment for Task Offloading in Mobile Edge Computing
In this paper, we consider a multiuser mobile edge computing (MEC) system, where a mixed-integer offloading strategy is used to assist the resource assignment for task offloading.
Wireless Quantized Federated Learning: A Joint Computation and Communication Design
The impact of the quantization error on the convergence time is evaluated and the trade-off among model accuracy and timely execution is revealed.
Optimization of Grant-Free NOMA with Multiple Configured-Grants for mURLLC
To support these requirements, the third generation partnership project (3GPP) has introduced enhanced grant-free (GF) transmission in the uplink (UL), with multiple active configured-grants (CGs) for URLLC UEs.
Channel modeling for in-body optical wireless communications
Moreover, we formulate a model for the calculation of the absorption coefficient of any generic biological tissue.
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.
Wireless Federated Learning (WFL) for 6G Networks -- Part II: The Compute-then-Transmit NOMA Paradigm
As it has been discussed in the first part of this work, the utilization of advanced multiple access protocols and the joint optimization of the communication and computing resources can facilitate the reduction of delay for wireless federated learning (WFL), which is of paramount importance for the efficient integration of WFL in the sixth generation of wireless networks (6G).
Wireless Federated Learning (WFL) for 6G Networks -- Part I: Research Challenges and Future Trends
Conventional machine learning techniques are conducted in a centralized manner.
Large Scale Global Optimization Algorithms for IoT Networks: A Comparative Study
To the best of the authors knowledge, this is the first time that LGSO algorithms are applied to the optimal power allocation problem in IoT networks.
On the Distribution of the Sum of Double-Nakagami-m Random Vectors and Application in Randomly Reconfigurable Surfaces
To facilitate the performance analysis of a RRS-assisted system, first, we present novel closed-form expressions for the probability density function, the cumulative distribution function, the moments, and the characteristic function of the distribution of the sum of double-Nakagami-m random vectors, whose amplitudes follow the double-Nakagami-m distribution, i. e., the distribution of the product of two Nakagami-m random variables, and phases follow the circular uniform distribution.
Information Theory Signal Processing Information Theory Applications
Learning based signal detection for MIMO systems with unknown noise statistics
Existing detection methods have mainly focused on specific noise models, which are not robust enough with unknown noise statistics.
Towards Optimally Efficient Search with Deep Learning for Large-Scale MIMO Systems
This indicates that the proposed algorithm reaches almost the optimal efficiency in practical scenarios, and thereby it is applicable for large-scale systems.
Non-Orthogonal Multiple Access (NOMA) With Multiple Intelligent Reflecting Surfaces
More importantly, simulation results reveal that a 3-bit resolution for discrete phase shifts is sufficient to achieve near-optimal outage performance.
Optimal Resource Allocation for Delay Minimization in NOMA-MEC Networks
We adopt the partial offloading policy, in which each user can partition its computation task into offloading and locally computing parts.
AnciNet: An Efficient Deep Learning Approach for Feedback Compression of Estimated CSI in Massive MIMO Systems
Accurate channel state information (CSI) feedback plays a vital role in improving the performance gain of massive multiple-input multiple-output (m-MIMO) systems, where the dilemma is excessive CSI overhead versus limited feedback bandwith.
Machine Learning in Nano-Scale Biomedical Engineering
Next, we discuss the state of the art ML methodologies that are used to countermeasure the aforementioned challenges.
All-Optical Cochlear Implants
In the present work, we introduce a novel cochlear implant (CI) architecture, namely all-optical CI (AOCI), which directly converts acoustic to optical signals capable of stimulating the cochlear neurons.
Analyzing Grant-Free Access for URLLC Service
Based on this framework, we define the latent access failure probability to characterize URLLC reliability and latency performances.
