The article analyzes the problem of energy efficient techniques in cooperative spectrum sensing (CSS). Although it was proven that single-device sensing is not sufficient for reliable sensing, cooperative spectrum sensing was proposed, burdened, however, with great overhead. Thus, work on the topic of energy efficient cooperative schemes gained more interest, which resulted in a number of energy efficient cooperative algorithm proposals. In this work, we try to classify the possible directions in energy efficient CSS and present a limited set of works introducing new ideas to an energy efficient CSS algorithm.

We present a new design concept for adaptive wireless communications with new trade-offs between system performance and energy consumption. The system performance, in terms of bit error rate, outage probability, and achieved spectral efficiency, depends on constellation signaling, applied diversity, and channel estimation. Resources dedicated to channel estimation and feedback traffic contribute to the overall system and network energy consumption, and the resulting CO₂ emission. We consider the trade-offs among different methodologies and parameters toward an energy-efficient green communication system design. Below, we discuss the degrees of freedom in the design of communications systems with imperfect channel estimation and diversity, and investigate their energy saving options. We present the case studies of single- and multicarrier systems applying both margin-adaptive and rate-adaptive pilot-assisted transmission.

We discuss dynamic spectrum aggregation methods, opportunities, and issues for future 5G communication in cognitive cellular networks. We focus on multicarrier technologies, which have been recognized as capable of flexible utilization of fragmented spectrum opportunities in unlicensed frequency bands, such as enhanced NC-OFDM and NC-FBMC. These techniques can be applied to shape the signal spectrum so that it is concentrated within used frequency bands, and the out-of-band transmitted power and associated interference generated to the incumbent coexisting systems are limited. We present key issues associated with spectrum aggregation that are recognized at the transmitter and the receiver. We also discuss solutions of these issues that can make spectrum aggregation viable for 5G systems.

As one of the promising branches of the Internet of Things, the cloud-enabled Internet of Vehicles (CE-IoV) is envisioned to serve as an essential data sensing, exchanging, and processing platform with powerful computing and storage capabilities for future intelligent transportation systems. The CE-IoV shows great promise for various emerging applications. In order to ensure uninterrupted and high-quality services, a vehicle should move with its own VM via live VM migration to obtain real-time location-based services. However, the live VM migration may lead to unprecedented location privacy challenges. In this article, we study location privacy issues and defenses in CE-IoV. We first present two kinds of unexplored VM mapping attacks, and thus design a VM identifier replacement scheme and a pseudonym-changing synchronization scheme to protect location privacy. We carry out simulations to evaluate the performance of the proposed schemes. Numerical results show that the proposed schemes are effective and efficient with high quality of privacy.

The concept of open radio access networks (RAN) creates numerous opportunities for developing new technology and economy branches. At the same time, a flexible and modular approach in the disaggregated RAN entails the need for careful design of the overall RAN architecture and the implementation and deployment process of new applications. It is assumed that dedicated and specialized software companies may deliver the latter. A joint effort must be guaranteed among different sectors (industry, academia, and standardization bodies) to make the whole process efficient, safe, and reliable. Here, one of the critical driving forces origins from the open-source community that often stimulates the development of a specific technology. In this paper, we address the challenges that have to be faced by third-party application developers in the context of Open RAN. Based on many implemented applications (called xApps or rApps), we compare various available solutions. We pose the most critical issues that must be tackled in the near future to stimulate the progress in open RAN development further. In particular, we compare available open platforms for xApp development and testing. We present the details of implementing four selected applications describing the problems encountered. The paper is split into two logical parts - first, we identify the key ambiguities related to the development of new xApps, which address more complicated use cases like beam management. In the second part, we present the challenges associated with detailed software implementation in existing open platforms. In the first case, we show that dedicated beam mobility management xApp can reduce beam switches and keep beam failures low. However, it requires access to detailed localization information. Similarly, the signaling storm detection xApp provides expected performance under the assumption that there is access to detailed information on, e.g., time advance resolution parameter. We conclude here that several aspects still need to be well-defined to allow smooth software implementation; these include the rules for data reporting in time, parameters available in service models, and localization features. Concerning the second logical part, related to low-level implementation, we compare the numerical results of the traffic steering and quality-of-service-based resource allocation xApps and draw conclusions related to implementation and testing. In particular, we point out problems associated with the simulator, the software, and conflicts inside. Finally, we identify the key challenges which should be treated as incentives for joint academia-industry cooperation in the field of Open RAN. Thus, the paper presents the lesson learned during the first years of xApp development.

In this article, we discuss a spectrum trading mechanism implemented by the spectrum broker in TV whitespaces. TVWS are spectrum frequency bands unused by DTV, interleaved in both frequency and space. Underutilization of these bands results from the fact that the DTV transmission systems now operational in the spectrum from 470 to 790 MHz are multifrequency systems employing high tower and high power network geometries, and must be managed for interference between transmitters. We motivate the use of a spectrum broker, an entity that manages the TVWS secondary spectrum market. Such a TVWS broker's responsibilities include planning the possible broad uses of the available spectrum in the TVWS; packaging the spectrum for short-term disposal through trading mechanisms; serving the broker's customers, with spectrum-leasing contracts; and acting as the port of call to handle interference caused by its customers to the primary DTV systems or between its customers themselves. We discuss the spectrum broker's merchant and auction modes for spectrum trading. In the merchant mode, the base price is decided by the allocation procedure, which considers various factors influencing the value of TVWS in a given place. In the auction mode, the customers' demands and bids decide the final price of the spectrum. We discuss the auction design and show results of the spectrum trading mechanisms, which have been successfully applied in a real-world test scenario in the area of Munich, Germany.