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Your search keyword '"Karagiannidis, George K."' showing total 31 results
Start Over Author "Karagiannidis, George K." Journal ieee wireless communications letters
31 results on '"Karagiannidis, George K."'

3. Proactive Resource Allocation for Aggregated VLC/RF Networks With Outdated CSI

Author

Bozanis, Dimitrios, Evgenidis, Nikos G., Papanikolaou, Vasilis K., Dowhuszko, Alexis A., Tegos, Sotiris A., Diamantoulaki, Panagiotis D., and Karagiannidis, George K.

Abstract

In this letter, the case of an aggregated VLC/RF network is presented, where the users can be served simultaneously by both a visible light communication (VLC) carrier and a radio-frequency (RF) carrier to increase their achievable data rate. The optimal resource allocation in the network is dependent on always having accurate channel state information (CSI), otherwise, in the case of outdated CSI, the system is prone to sub-optimally allocating resources and, due to the limited coverage of VLC, users may also experience outage. A closed-form expression for the coverage probability is presented for a user moving randomly in the cell. Using this, a proactive resource allocation algorithm is proposed that takes into account outdated CSI which can occur due to user movement, and ensures the outage probability is low in the network without diminishing the average achievable data rate of users. Finally, simulation results validate the proposed analysis and showcase the effectiveness of this approach.

Published
2024
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4. Energy-Efficient Optimization for Mobile Edge Computing With Quantum Machine Learning

Author

Adu Ansere, James, Tran, Dung T., Dobre, Octavia A., Shin, Hyundong, Karagiannidis, George K., and Duong, Trung Q.

Abstract

We investigate the joint optimization problem of stochastic computation offloading, content caching strategy, and dynamic resource allocation to maximize the energy efficiency of mobile edge computing in Internet-of-Things. Specifically, we propose a quantum deep reinforcement learning algorithm to exponentially increase the caching learning speed and content caching delivery efficiency in multi-dimensional continuous and large action spaces. Furthermore, we utilize the modified Grover’s algorithm with faster computation time to improve the processing efficiency and data-content retrieval for transition quantum state probabilities. The numerical results show that our proposed quantum machine learning scheme significantly outperforms other benchmarks in terms of energy-efficiency maximization subject to transmission power, energy consumption, and transmission latency.

Published
2024
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5. Improved Bayesian Learning Detectors for Uplink Grant-Free MIMO-NOMA

Author

Yang, Boran, Zhang, Xiaoxu, Hao, Li, and Karagiannidis, George K.

Abstract

Grant-free non-orthogonal multiple access (GF-NOMA) and multiple-input multiple-output (MIMO) techniques are key enablers for massive machine-type communications (mMTC) in 5G cellular Internet of Things. On the other hand, compressed sensing (CS) is widely accepted for multiuser detection, due to the sporadic traffic of mMTC. In this letter, we propose two Bayesian-based CS algorithms for uplink grant-free MIMO-NOMA. Exploiting the iterative expectation maximization (EM) and maximum ratio combining techniques, the spatially enhanced sparse Bayesian learning (SE-SBL) algorithm is developed to alternately update hyperparameter values and combined observation signals. Furthermore, we embed the generalized approximate message passing technique into the SE-SBL and propose a low-complexity computational approach. In particular, the aforementioned Bayesian algorithms do not require any prior knowledge of user activity level and noise power. Simulation results show that the proposed Bayesian methods exhibit a superior performance gain over the state-of-the-art.

Published
2023
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24. Level Crossing Rate and Average Fade Duration in <inline-formula> <tex-math notation="LaTeX">$\mathcal{F}$ </tex-math></inline-formula> Composite Fading Channels

Author

Yoo, Seong Ki, Cotton, Simon L., Sofotasios, Paschalis C., Muhaidat, Sami, and Karagiannidis, George K.

Abstract

In this letter, we derive exact closed-form expressions for the level crossing rate (LCR) and average fade duration (AFD) of the signal envelope in $\mathcal {F}$ composite fading channels. Using the novel expressions, we then investigate the behavior of the LCR and AFD for different multipath fading and shadowing conditions. It is shown that multipath fading has a more significant effect on the LCR at lower fade levels while shadowing tends to have a discernible impact on higher threshold levels. In contrast, shadowing has a more noticeable effect on the AFD compared to multipath fading at both lower and higher levels. Approximate expressions for the LCR and AFD are also provided, and shown to be in good agreement with the exact LCR and AFD as they approach lower and higher threshold levels. The offered results are expected to be useful in the design of emerging systems such as device-to-device communications.

Published
2020
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31. A Low-Complexity Detector for BPPM Systems Under Additive Gaussian Mixture Noise

Author

Ataloglou, Vasileios G., Ntouni, Georgia D., Kapinas, Vasileios M., and Karagiannidis, George K.

Abstract

We analyze the performance of the single-threshold detector (STD) for binary pulse position modulation in the presence of symmetric Gaussian mixture noise (GMN). We first derive a general closed-form expression for the average error probability that is later used to investigate the optimality of the STD with zero threshold, which is the simplest form of STD. We also establish conditions sufficient to guarantee minimum error rates with the low-complexity STD for a wide range of signal-to-noise ratio. The theoretical results are verified through simulations of GMN with various noise parameters.

Published
2017
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