Cooperative Sensing and Allocation Algorithm of Cognitive Radio Spectrum Based on Artificial Intelligence

In recent years, with the rapid development of artificial intelligence technology, people’s demand for wireless spectrum resources is increasing, which poses a huge challenge to the originally tight and limited wireless spectrum resources. On the other hand, the traditional fixed spectrum cooperative sensing and allocation algorithms result in extremely low spectrum utilization for a considerable part of the licensed spectrum. The purpose of this paper is to study the cooperative sensing and allocation algorithm of cognitive RS (radio spectrum) based on artificial intelligence. This dissertation focuses on cooperative perception and cognitive radio systems, respectively, from the aspects of cooperative perception of user fairness, maximization of system energy efficiency, and user detection when user access is busy. Firstly, a joint optimization model of fairness cooperative spectrum sensing and allocation is established to compensate the sensing overhead of cooperative users to ensure its fairness; then, define and analyze the energy efficiency of the cognitive system, and establish a joint optimization model of cooperative spectrum sensing and allocation based on artificial intelligence to maximize energy efficiency, and optimize wireless sensing and allocation parameters while ensuring maximum system energy efficiency. The experimental results show that when = 0.7, the algorithm proposed in this study has reached 100% of the RS perception performance, while the traditional algorithm only has 93%. The algorithm proposed in this paper has greater advantages in perception and distribution performance.

Multi-Session Multicasting for 360-Degree Video Multicast over OFDMA Systems

360-degree video content provides a rich and immersive multimedia experience to viewers by allowing viewers to the video from any angle. However, 360-degree videos require much higher bandwidth to be delivered over mobile networks compared to conventional videos. Multicasting of the videos is one of the solutions to efficiently utilize the limited bandwidth since many viewers share the wireless spectrum resource for popular videos, such as sports events or musical concerts. LTE eMBMS assigns the videos to the video sessions, and multiple viewers can subscribe to the same video allocated to the video sessions. Moreover, the tiling of the 360-degree video makes it possible to control the regional quality of the video. The tiles that are likely to be seen by many viewers should have higher quality than other tiles to satisfy more viewers. In this paper, we proposed the Multi-Session Multicast (MSM) system to optimally allocate the wireless resources to tiles with different qualities to maximize the expected user experience. The experimental results show that the proposed MSM system provides higher quality videos to viewers using limited wireless resources.

The Parable of the Auctioneer: Complexity in Paul R. Milgrom’s Discovering Prices

Designing marketplaces in complex settings requires both novel economic theory and real-world engineering, often drawing upon ideas from fields such as computer science and operations research. In Discovering Prices: Auction Design in Markets with Complex Constraints, Milgrom (2017) explains the theory and design of the United States’ “incentive auction” that reallocated wireless spectrum licenses from television broadcasters to telecoms. Milgrom’s account teaches us how economic designers can grapple with complexity both in theory and in practice. Along the way, we come to understand several different types of complexity that can arise in marketplace design. (JEL D43, D44, D47, L96, L98)

Cognitive Radio Networks and Spectrum Sensing: A Review

<p class="0abstract"><span lang="EN-US">The wireless spectrum demand is at a constant rise in contrast to its scarcity. Cognitive Radio Networks(CRN’s) as a notion was first brought into the light to tackle this issue. A CRN is an intelligent network that dynamically changes its characteristics through the process of Spectrum Sensing and adapts to the convenience of the environment it is in. This article presents a basic overview of what CRN’s are. The major contributions of this paper lie in a comparative study of CRN’s and Spectrum Sensing in recent years as well as its main challenges and applications. This review shall help current and new researchers in the field to look for future outlooks and give them a basic run-through of CRN’s and Spectrum Sensing and their characteristics. </span></p>

The Value of Sharing Intermittent Spectrum

We examine a model of Cournot competition with congestion motivated by recent policy to allow commercial sharing of wireless spectrum that is assigned to other users such as government agencies. A key feature of such spectrum is that it is intermittently available because of the incumbent user’s activity. In our model, wireless service providers (SPs) compete for a common pool of customers using their own proprietary (exclusively licensed) bands of spectrum along with access to an additional intermittent band. When the intermittent band is unavailable, any traffic carried on that band must be shifted to the proprietary bands. Customers are sensitive to both the price they pay and the average congestion they experience across the bands of spectrum from which they receive service. We compare two different access policies for this intermittent band: one in which it is open to all SPs and one in which it is licensed to a single SP. We also allow the band to be divided into multiple subbands where each subband is either open or licensed. We characterize trade-offs between social welfare and consumer welfare that depend on the choice of different access policies and assignments of subbands to SPs. These can involve subtle issues related to the ability of a larger SP to make more efficient use of intermittent spectrum and the increase in competition by assigning more spectrum to smaller SPs. This paper was accepted by David Simchi-Levi, operations management.