Search Results for author: George K. Karagiannidis

Found 17 papers, 2 papers with code

Learning to Optimize Resource Assignment for Task Offloading in Mobile Edge Computing

no code implementations15 Mar 2022 Yurong Qian, Jindan Xu, Shuhan Zhu, Wei Xu, Lisheng Fan, George K. Karagiannidis

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

no code implementations11 Mar 2022 Pavlos S. Bouzinis, Panagiotis D. Diamantoulakis, George K. Karagiannidis

The impact of the quantization error on the convergence time is evaluated and the trade-off among model accuracy and timely execution is revealed.

Federated Learning Quantization

Optimization of Grant-Free NOMA with Multiple Configured-Grants for mURLLC

no code implementations17 Nov 2021 Yan Liu, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan, George K. Karagiannidis

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

no code implementations3 Nov 2021 Stylianos E. Trevlakis, Alexandros-Apostolos A. Boulogeorgos, Nestor D. Chatzidiamantis, George K. Karagiannidis

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

no code implementations3 Jun 2021 Tianqi Mao, Jiaxuan Chen, Qi Wang, Chong Han, Zhaocheng Wang, George K. Karagiannidis

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

no code implementations24 Apr 2021 Pavlos S. Bouzinis, Panagiotis D. Diamantoulakis, George K. Karagiannidis

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).

Federated Learning

Large Scale Global Optimization Algorithms for IoT Networks: A Comparative Study

no code implementations22 Feb 2021 Sotirios K. Goudos, Achilles D. Boursianis, Ali Wagdy Mohamed, Shaohua Wan, Panagiotis Sarigiannidis, George K. Karagiannidis, Ponnuthurai N. Suganthan

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

no code implementations10 Feb 2021 Sotiris A. Tegos, Dimitrios Tyrovolas, Panagiotis D. Diamantoulakis, George K. Karagiannidis

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

1 code implementation21 Jan 2021 Ke He, Le He, Lisheng Fan, Yansha Deng, George K. Karagiannidis, Arumugam Nallanathan

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

1 code implementation7 Jan 2021 Le He, Ke He, Lisheng Fan, Xianfu Lei, Arumugam Nallanathan, George K. Karagiannidis

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

no code implementations31 Oct 2020 Yanyu Cheng, Kwok Hung Li, Yuanwei Liu, Kah Chan Teh, George K. Karagiannidis

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

no code implementations11 Sep 2020 Fang Fang, Yanqing Xu, Zhiguo Ding, Chao Shen, Mugen Peng, George K. Karagiannidis

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

no code implementations17 Aug 2020 Yuyao Sun, Wei Xu, Lisheng Fan, Geoffrey Ye Li, George K. Karagiannidis

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.

All-Optical Cochlear Implants

no code implementations20 Jun 2020 Stylianos E. Trevlakis, Alexandros-Apostolos A. Boulogeorgos, Nestor D. Chatzidiamantis, George K. Karagiannidis

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

no code implementations18 Feb 2020 Yan Liu, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan, George K. Karagiannidis

Based on this framework, we define the latent access failure probability to characterize URLLC reliability and latency performances.

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