The article describes the potential gain by spectrum sharing between cellular operators in terms of network efficiency. The focus of the study is on a specific resource sharing scenario: spectrum sharing between two operators in cellular downlink transmission. If frequency bands are allocated dynamically and exclusively to one operator - a case called orthogonal spectrum sharing - significant gains in terms of achievable throughput (spectrum sharing gains between 50 percent and 100 percent) and user satisfaction are reported for asymmetric scenarios at link and system level as well as from two hardware demonstrators. Additionally, if frequency bands are allocated simultaneously to two operators - a case called non-orthogonal spectrum sharing - further gains are reported. In order to achieve these, different enablers from hardware technologies and base station capabilities are required. However, we argue that all requirements are fulfilled in 3GPP and newer mobile standards. Therefore, the results and conclusions of this overview article encourage to seriously consider the inter-operator spectrum sharing technologies
Over the years, radio resource management has been benchmarked mostly by its technical merits. A service provider, however, must also reckon with economics. When the financial needs of the provider and the satisfaction of the users are considered, common objectives in radio resource management, like maximising throughput or meeting various quality constraints, may no longer be sufficient. We analyse next generation communication systems by including models of economics, which have been presented in the literature, and reasonable considerations to depict the users/provider relationship in a generalised multimedia environment. In particular, we develop a model of users' satisfaction, in which both requested quality of service and price paid are taken into account. The model enables us to investigate how resource allocation dynamics affect operator revenues and to derive some useful insights. Radio resource management can be shown to be highly dependent on economic considerations. The provider's task to determine the best usage of the network capacity is heavily affected by the users' service demand and their reactions to the pricing policy. Thus, the economic scenario needs to be taken into account to exploit the constrained radio resource efficiently. The model is applied to a CDMA cellular system
Energy Harvesting Wireless Sensor Devices are increasingly being considered for deployment in sensor networks, due to their demonstrated advantages of prolonged lifetime and autonomous operation. However, irreversible degradation mechanisms jeopardize battery lifetime, calling for intelligent management policies, which minimize the impact of these phenomena while guaranteeing a minimum Quality of Service (QoS). This paper explores a mathematical characterization of these devices, focusing on the interplay between the battery discharge policy and the irreversible degradation of the storage capacity. We propose a stochastic Markov chain framework, suitable for policy optimization, which captures the degradation status of the battery. We present a general result of Markov chains, which exploits the timescale separation between the communication time-slot of the device and the battery degradation process, and enables an efficient optimization. We show that this model fits well the behavior of real batteries for what concerns their storage capacity degradation over time. We demonstrate that a degradation-aware policy significantly improves the lifetime of the sensor compared to "greedy" policies, while guaranteeing the minimum required QoS. Finally, a simple heuristic policy, which never discharges the battery below a given threshold, is shown to achieve near-optimal performance in terms of battery lifetime
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