Spectrum Trading: An Abstracted Bibliography

This document contains a bibliographic list of major papers on spectrum trading and their abstracts. The aim of the list is to offer researchers entering this field a fast panorama of the current literature. The list is continually updated on the webpage \url{http://www.disp.uniroma2.it/users/naldi/Ricspt.html}. Omissions and papers suggested for inclusion may be pointed out to the authors through e-mail (\textit{[email protected]})

Analysis of Radio Spectrum Market Evolution Possibilities

A tremendous growth in wireless traffic volumes and a shortage of feasible radio spectrum has led to a situation where the old and rigid spectrum regime is not a viable option for spectrum management and a shift towards a more market driven approach has begun. Great uncertainty still exists over how such a radio spectrum market will come about and what kind of shape it would take. This paper studies some long term macro level evolution possibilities for how this radio spectrum market could emerge and what would be the corresponding value chain configurations. The scenario planning and system dynamics methods are utilized to build four alternative future spectrum market scenarios.Spectrum Markets, Spectrum Policy, Flexible Spectrum Usage, Cognitive Radio, Value Networks, Scenario Planning, System Dynamics.

Spectrum Sharing Optimization and Analysis in Cellular Networks under Target Performance and Budget Restriction

Dynamic Spectrum Sharing (DSS) aims to provide opportunistic access to under-utilised spectrum in cellular networks for secondary network operators. In this paper we propose an algorithm using stochastic and optimisation models to borrow spectrum bandwidths under the assumption that more resources exist for secondary access than the secondary network demand by considering a merchant mode. The main aim of the paper is to address the problem of spectrum borrowing in DSS environments, where a secondary network operator aims to borrow the required spectrum from multiple primary network operators to achieve a maximum profit under specific grade of service (GoS) and budget restriction. We assume that the primary network operators offer spectrum access opportunities with variable number of channels (contiguous and/or non-contiguous) at variable prices. Results obtained are then compared with results derived from an algorithm in which spectrum borrowing are random. Comparisons showed that the gain in the results obtained from our proposed stochastic-optimisation framework is significantly higher than random counterpart

NOMA based resource allocation and mobility enhancement framework for IoT in next generation cellular networks

With the unprecedented technological advances witnessed in the last two decades, more devices are connected to the internet, forming what is called internet of things (IoT). IoT devices with heterogeneous characteristics and quality of experience (QoE) requirements may engage in dynamic spectrum market due to scarcity of radio resources. We propose a framework to efficiently quantify and supply radio resources to the IoT devices by developing intelligent systems. The primary goal of the paper is to study the characteristics of the next generation of cellular networks with non-orthogonal multiple access (NOMA) to enable connectivity to clustered IoT devices. First, we demonstrate how the distribution and QoE requirements of IoT devices impact the required number of radio resources in real time. Second, we prove that using an extended auction algorithm by implementing a series of complementary functions, enhance the radio resource utilization efficiency. The results show substantial reduction in the number of sub-carriers required when compared to conventional orthogonal multiple access (OMA) and the intelligent clustering is scalable and adaptable to the cellular environment. Ability to move spectrum usages from one cluster to other clusters after borrowing when a cluster has less user or move out of the boundary is another soft feature that contributes to the reported radio resource utilization efficiency. Moreover, the proposed framework provides IoT service providers cost estimation to control their spectrum acquisition to achieve required quality of service (QoS) with guaranteed bit rate (GBR) and non-guaranteed bit rate (Non-GBR)