Journal papers:
[J.1] M. Di Renzo, A. Zappone, T. T. Lam, M. Debbah, “System-Level Modeling and Optimization of the Energy Efficiency in Cellular Networks—A Stochastic Geometry Framework”, IEEE Transactions on Wireless Communications, 2018
[J.2] A. Zappone, L. Sanguinetti, M. Debbah, “Energy-Delay Efficient Power Control in Wireless Networks”, IEEE Transactions on Communications, 2018
[J.3] S. D'Oro, A. Zappone, S. Palazzo, M. Lops, “A Learning Approach for Low-Complexity Optimization of Energy Efficiency in Multicarrier Wireless Networks”, IEEE Transactions on Wireless Communications, 2018
[J.4] M. Sinaie, P.-H. Lin, A. Zappone, P. Azmi, E. A. Jorswieck, “Delay-Aware Resource Allocation for 5G Wireless Networks With Wireless Power Transfer”, IEEE Transactions on Vehicular Technology, 2018
[J.5] A. Zappone, M. Di Renzo, M. Debbah, “Wireless Networks Design in the Era of Deep Learning: Model-Based, AI-Based, or Both?”, IEEE Transactions on Communications, 2019
[J.6] A. Zappone, M. Di Renzo, M. Debbah, T. T. Lam, X. Qian, “Model-Aided Wireless Artificial Intelligence: Embedding Expert Knowledge in Deep Neural Networks Towards Wireless Systems Optimization”, IEEE Vehicular Technology Magazine, 2019
Conference papers:
[C.1] M. Di Renzo, A. Zappone, T. T. Lam, M. Debbah, “Stochastic Geometry Modeling of Cellular Networks: A New Definition of Coverage and Its Application to Energy Efficiency Optimization”, EUSIPCO 2018
[C.2] S. D'Oro, A. Zappone, S. Palazzo, M. Lops, “A learning-based approach to energy efficiency maximization in wireless networks”, WCNC 2018
[C.3] M. Sinaie, P.-H. Lin, A. Zappone, P. Azmi, E. A. Jorswieck, “Resource Allocation in OFDM-Based SWIPT with Statistical Delay Constraints”, GLOBECOM 2017
[C.4] A. Zappone, M. Debbah, Z. Altman, “Online Energy-Efficient Power Control in Wireless Networks by Deep Neural Networks”, SPAWC 2018
[C.5] A. Zappone, L. Sanguinetti, M. Debbah, “User Association and Load Balancing for Massive MIMO through Deep Learning”, ASILOMAR 2018
[C.6] L. Sanguinetti, A. Zappone, M. Debbah, “Deep Learning Power Allocation in Massive MIMO”, ASILOMAR 2018
All publications are freely available either on Arxiv or on ResearchGate. The system setup is that of a multi-cellular network, as shown in Fig. 1. The goal is to determine the optimal transmit power of each node to maximize the energy efficiency of the whole network or of a single communication link, defined as the ratio between the amount of bits that the link/network can transmit without errors and the corresponding energy consumption.
In [J.1] [C.1] new models for energy efficiency in 5G cellular networks are developed. It is proved that a single optimal base station density and a corresponding single optimal transmit power value exist in order to maximize the energy efficiency.
[J.2] employs the tool of game theory to model the interactions among non-cooperating nodes in a distributed network, proveing that a single equilibrium point exists and also providing an algorithm to reach it. However, at the equilibrium a gap exists with respect to the network energy efficiency that could be achieved if all terminals cooperated with each other.
[J.3] [C.2] aim at closing the gap evidenced in [J.2]. An improved power control algorithm is proposed that enjoys near-optimal performance, with a significantly lower complexity than state-of-the-art approaches.
[J.4] [C.3] studies wireless power transfer among devices in a 5G network. Each device transmits both an informational signal and energy signal for the receiver. An algorithm is developed to compute the optimal split between the two signals and perform optimal power allocation among the network nodes.
[J.5] [J.6] [C.4] [C.5] [C.6] investigate the use of AI with wireless networks. It is shown that the joint use of AI and of mathematical modeling improves the performance-complexity trade-offs compared to available methods.
Major exploitation and dissemination activities:
1) Three technical workshops at the international conferences:
a) IEEE PIMRC 2019
b) European Wireless 2018
c) ISWCS 2018
2) Two panels aimed at both technical and non-technical audience at the international conferences
a) BalkanCom 2019
b) WMNC 2019
3) WMNC 2019 conference organized by Prof. Debbah and the ER. The conference featured talks from leading researchers on AI for wireless networks.
4) Technical tutorial given the at international conferences:
a) IEEE WCNC 2019.
b) IEEE ICC 2019.
c) EUSIPCO 2019
5) Open Doors event at the HO for school and master students in December 2017
