01631nas a2200145   4500008004100000245007900041210006900120520104400189100002401233700002101257700002401278700002201302700002601324856013501350       2022                        eng d00aA Game Theoretic Approach for Efficient Resource Allocation in 5G Networks0 aGame Theoretic Approach for Efficient Resource Allocation in 5G 3 aHeterogeneous Networks (HetNets) have been lauded as a key technology for 5G communications, enabling fast growth in mobile traffic. HetNets may also expand the network’s capacity and serve more users. However, interference between small cells and macro-cells makes Quality of Service (QoS) more difficult to achieve, and thus novel protocols, new technologies, and future trends should also be included in order to provide efficiency in Resource Allocation (RA). Game Theory (GT) concepts have been widely used in a variety of engineering design challenges in which one component’s activity affects and perhaps conflicts with the actions of other components. As a result, game formulations are utilized, and the idea of equilibrium is applied to find a stable solution for the participants. In this paper, we compare two algorithms used for RA, the first being a classical RA algorithm and the second being a game theoretic one. The game implemented is called “Tragedy of the Commons”, and is applied in a non-cooperative network.1 aKoukouvela, Aspasia1 aBouras, Christos1 aKokkinos, Vasileios1 aGkamas, Apostolos1 aPouyioutas, Philippos  uhttp://telematics.upatras.gr/telematics/publications/game-theoretic-approach-efficient-resource-allocation-5g-networks?language=el01783nas a2200145   4500008004100000245007000041210006900111520122000180100001801400700002101418700002201439700002401461700002401485856012801509       2022                        eng d00aResource Allocation In 5G and Beyond Networks for Mu-MIMO Systems0 aResource Allocation In 5G and Beyond Networks for MuMIMO Systems3 aThe resource allocation problem focuses on finding an optimal allocation of a specific number of resources to maintain Quality of Service (QoS). That is where Multiple-Input Multiple-Output (MIMO) come in as a radio antenna technology. In order to, optimize data speed, minimize errors and improve the radio transmission capacity MIMO utilizes multiple antennas at both the transmitter and the receiver. This technology uses a variety of antennas and paths that carry the data. Each antenna uses different paths. Multi-user MIMO (mu-MIMO) stands for a technology that allows routers to communicate simultaneously with multiple endpoint devices and it is the next evolutionary step of single user MIMO. Over the past decade, significant advances have been made to improve the performance of mu-MIMO. Although non-negligible progress has been achieved so far, optimal algorithms for Resource Allocation (RA) will help better the performance of mu-MIMO by increasing the system’s performance in terms of throughput, fairness, and QoS. The purpose of this paper is to provide a comparison of different beamforming techniques used for resource allocation and list them in ascending order depending on their efficiency.1 aBarri, Eirini1 aBouras, Christos1 aGkamas, Apostolos1 aKokkinos, Vasileios1 aKoukouvela, Aspasia  uhttp://telematics.upatras.gr/telematics/publications/resource-allocation-5g-and-beyond-networks-mu-mimo-systems?language=el01562nas a2200133   4500008004100000245009200041210006900133520099900202100001801201700002101219700002401240700002401264856014001288       2021                        eng d00aA Mechanism for Improving the Spectral Efficiency in mu-MIMO for 5G and Beyond Networks0 aMechanism for Improving the Spectral Efficiency in muMIMO for 5G3 aThe ultimate challenge that arises in 6G and 5G and beyond networks is how the mobile networks of the future will be able to cope with the constantly increasing number of devices. In Multiuser Multiple-Input and Multiple-Output (mu-MIMO), the base station basically serves many users at the same time using the same frequency. The topic considered in this paper is the spectral performance in Downlink mu-MIMO. This paper’s goal is to improve the achieved spectral efficiency of the communication system, as well as the achieved reliability of the communication link. An algorithm based on downlink scheduling and the resource allocation is proposed to achieve maximum spectral use of the system. Considering user’s demands, this paper’s mechanism is able to allocate the potential user of the queue to the ”best antenna” based on its demands and distance. That provokes a larger number of devices that can be supported, always according to the specifications stated in IEEE 802.11ax.1 aBarri, Eirini1 aBouras, Christos1 aKokkinos, Vasileios1 aKoukouvela, Aspasia  uhttp://telematics.upatras.gr/telematics/publications/mechanism-improving-spectral-efficiency-mu-mimo-5g-and-beyond-networks?language=el