The exploitation of millimeter wave (mmWave) and sub-Terahertz (sub-THz) bands is expected to be one of the main pillars for the development of future cellular networks due to the high available bandwidth they provide. The existence of Line-of-Sight (LOS) link between a user equipment (UE) and an access point (AP) is a prerequisite for connection establishment in these networks, as the wireless links in these bands are very sensitive to blockage effects. This can be achieved by densifying APs within a network area. An arising challenge is the efficient exploitation of the available bandwidth of a given network. In this paper, the maximization of the number of served UEs in modern mmWave and sub-THz cellular networks is investigated and achieved by deploying a Maximum Flow Algorithm for UE-AP association (MFUA) to optimize bandwidth allocation, assuming that every AP will have a finite and predefined amount of bandwidth which they can share among UEs. MFUA determines the maximum flow between two given nodes of a graph corresponding to a specific network, where the capacity of its edges is known. An extensive simulation campaign was carried out revealing that the use of MFUA utilizes bandwidth more effectively compared to the reference method and improves the system performance, leading to the maximization of number of served UEs. The examined test cases include static and time-evolving scenarios.

Future wireless networks need to support the increasing demands for high data rates and improved coverage. One promising solution is sectorization, where an infrastructure node is equipped with multiple sectors employing directional communication. Although the concept of sectorization is not new, it is critical to fully understand the potential of sectorized networks, such as the rate gain achieved when multiple sectors can be simultaneously activated. In this paper, we focus on sectorized wireless networks, where sectorized infrastructure nodes with beam-steering capabilities form a multi-hop mesh network. We present a sectorized node model and characterize the capacity region of these sectorized networks. We define the flow extension ratio and the corresponding sectorization gain, which quantitatively measure the performance gain introduced by node sectorization as a function of the network flow. Our objective is to find the sectorization of each node that achieves the maximum flow extension ratio, and thus the sectorization gain. Towards this goal, we formulate the corresponding optimization problem and develop an efficient distributed algorithm that obtains the node sectorization under a given network flow with an approximation ratio of 2/3. Additionally, we emphasize the class of Even Homogeneous Sectorizations, which simultaneously enhances the efficiency of dynamic routing schemes with unknown arrival rates and increases network capacity. We further propose that if sectorization can be adapted dynamically over time, either a backpressure-driven or maximum weighted b-matching-based routing approach can be employed, thereby expanding the achievable capacity region while preserving stability under unknown traffic conditions. Through extensive simulations, we evaluate the sectorization gain and the performance of the proposed algorithms in various network scenarios.

We study the problem of operating a quantum switch with memory constraints. In particular, the switch has to allocate quantum memories to clients to generate link-level entanglements (LLEs), and then use these to serve end-to-end entanglements requests. The paper’s main contributions are (i) to characterize the switch’s capacity region and study how it scales with respect to the number of quantum memories and probability of successful LLEs and (ii) to propose a memory allocation policy that is throughput optimal. In addition, when the requests are bipartite and the LLE attempts are always successful, we show that the proposed policy has polynomial time complexity. We evaluate the proposed policy numerically and illustrate its performance depending on the requests arrivals characteristics and the time available to obtain a memory allocation.

Towards addressing spectral scarcity and enhancing resource utilization in 5G networks, network slicing is a promising technology to establish end-to-end virtual networks without requiring additional infrastructure investments.By leveraging Software Defined Networks (SDN) and Network Function Virtualization (NFV), we can realize slices completely isolated and dedicated to satisfy the users' diverse Quality of Service (QoS) prerequisites and Service Level Agreements (SLAs).This paper focuses on the technical and economic challenges that emerge from the application of the network slicing architecture to real-world scenarios.We consider a market where multiple Network Providers (NPs) own the physical infrastructure and offer their resources to multiple Service Providers (SPs).Then, the SPs offer those resources as slices to their associated users.We propose a holistic iterative model for the network slicing market along with a clock auction that converges to a robust ǫ-competitive equilibrium.At the end of each cycle of the market, the slices are reconfigured and the SPs aim to learn the private parameters of their users.Numerical results are provided that validate and evaluate the convergence of the clock auction and the capability of the proposed market architecture to express the incentives of the different entities of the system.

Future wireless networks need to support the increasing demands for high data rates and improved coverage. One promising solution is sectorization, where an infrastructure node (e.g., a base station) is equipped with multiple sectors employing directional communication. Although the concept of sectorization is not new, it is critical to fully understand the potential of sectorized networks, such as the rate gain achieved when multiple sectors can be simultaneously activated. In this paper, we focus on sectorized wireless networks, where sectorized infrastructure nodes with beam-steering capabilities form a multi-hop mesh network for data forwarding and routing. We present a sectorized node model and characterize the capacity region of these sectorized networks. We define the flow extension ratio and the corresponding sectorization gain, which quantitatively measure the performance gain introduced by node sectorization as a function of the network flow. Our objective is to find the optimal sectorization of each node that achieves the maximum flow extension ratio, and thus the sectorization gain. Towards this goal, we formulate the corresponding optimization problem and develop an efficient distributed algorithm that obtains the node sectorization under a given network flow with an approximation ratio of 2/3. Through extensive simulations, we evaluate the sectorization gain and the performance of the proposed algorithm in various network scenarios with varying network flows. The simulation results show that the approximate sectorization gain increases sublinearly as a function of the number of sectors per node.

In this paper, to exploit the challenges and potential offered by the simultaneous use of non-orthogonal multiple access (NOMA) and orthogonal frequency division multiple access (OFDMA) transmission options in future 5G wireless systems, we aim at the proper modeling and transformation of the uplink power allocation problem. In particular, in this setting, each user has two degrees of freedom in the decision making process, namely its overall transmission power level, and the corresponding power investment to the OFDMA and/or NOMA based transmissions. The resulting multi-variable power allocation problem is treated and solved under three different perspectives, namely: 1) Games in Normal Form and Nash Equilibrium (NE); 2) Optimization techniques targeting system social welfare through a centralized optimal solution; and 3) Games in Satisfaction Form and Efficient Satisfaction Equilibrium (ESE). Based on these approaches, different solutions and stable operation points are identified and their properties are analyzed. An in depth evaluation and comparison of the various obtained outcomes is achieved, via modeling and simulations. The focus is placed on the impact and the interplay of the NOMA specific features, including the potential over-exploitation of the available bandwidth, the fairness in accessing it, and the interference treatment. It is also shown that, using the satisfaction form games for the users to converge to the ESE, provides an efficient and promising user-centric modeling approach to the power allocation problem, as the system adapts to the users’ application needs, while at the same time eliminates a significant amount of interference.