Most existing studies of spectrum usage have been performed by actively sensing the energy levels in specific RF bands including cellular bands. In this paper, we provide a unique, complementary analysis of cellular primary usage by analyzing a dataset collected inside a cellular network operator. One of the key aspects of our dataset is its scale – it consists of data collected over three weeks at hundreds of base stations. We dissect this data along different dimensions to characterize and model primary usage as well as understand its temporal and spatial variations. Our analysis reveals several results that are relevant if Dynamic Spectrum Access (DSA) approaches are to be deployed for cellular frequency bands. For instance, we find that call durations show significant deviations from the oftenused exponential distribution, which makes call-based modeling more complicated. We also show that a random walk process, which does not use call durations, can often be used for modeling the aggregate cell capacity. Furthermore, we highlight some applications of our results to improve secondary usage of licensed spectrum.

Abstract — We design truthful double spectrum auctions where multiple parties can trade spectrum based on their individual needs. Open, market-based spectrum trading motivates existing spectrum owners (as sellers) to lease their selected idle spectrum to new spectrum users, and provides new users (as buyers) the spectrum they desperately need. The most significant challenge is how to make the auction economic-robust (truthful in particular) while enabling spectrum reuse to improve spectrum utilization. Unfortunately, existing designs either do not consider spectrum reuse or become untruthful when applied to double spectrum auctions. We address this challenge by proposing TRUST, a general framework for truthful double spectrum auctions. TRUST takes as input any reusability-driven spectrum allocation algorithm, and applies a novel winner determination and pricing mechanism to achieve truthfulness and other economic properties while significantly improving spectrum utilization. To our best knowledge, TRUST is the first solution for truthful double spectrum auctions that enable spectrum reuse. Our results show that economic factors introduce a tradeoff between spectrum efficiency and economic robustness. TRUST makes an important contribution on enabling spectrum reuse to minimize such tradeoff. I.

Abstract—In this paper, we address the spectrum allocation problem in cellular networks under the coordinated dynamic spectrum access (CDSA) model. In this model, a centralized spectrum broker owns a part of the spectrum and issues dynamic spectrum leases to competing base stations in the region it controls. We consider a dynamic auction based approach where the base stations bid for channels depending on their demands. The broker allocates channels to them with an objective to maximize the overall revenue generated subject to wireless interference in the network. This problem is known to be NP-hard and has been addressed before in limited context. We address this problem in a very generic context where (i) interference in the network is modeled using pairwise and physical interference models and (ii) base stations can bid for heterogeneous channels of different width using generic bidding functions. We propose efficient approximation algorithms that give near optimal solutions with provable analytical bounds. Detailed simulation studies using randomly generated and real base station networks show that our algorithms scale very well for large network sizes. I.

Traditionally, interference protection is guaranteed through a policy of spectrum licensing, whereby wireless systems get exclusive access to spectrum. This is an effective way to prevent interference, but it leads to highly inefficient use of spectrum. Cognitive radio along with software radio, spectrum sensors, mesh networks, and other emerging technologies can facilitate new forms of spectrum sharing that would greatly improve spectral efficiency and alleviate scarcity, if spectrum policies are in place that support these forms of sharing. On the other hand, new technology that is inconsistent with spectrum policy will have little impact. This paper discusses policies that can enable or facilitate the use of many spectrum-sharing arrangements, where spectrumsharing arrangements are categorized as being based on either coexistence or cooperation, and as either sharing among equals or primary-secondary sharing. A shared band of spectrum may be managed directly by the regulator, or this responsibility may be delegated in large part to a license-holder. The type of sharing arrangement and the entity that manages it have great impact on which technical approaches are viable and effective. The most efficient and cost-effective form of spectrum sharing will depend on the type of systems involved, where systems under current consideration are as diverse as television broadcasters, cellular carriers, public safety systems, point-to-point links, and personal and local-area networks. In addition, while cognitive radio offers policy-makers the opportunity to improve spectral efficiency, cognitive radio also provides new challenges for enforcement of policies. A responsible regulator will not allow a device into the marketplace that might harm other systems. Thus, designers must seek innovative ways to assure regulators that new devices will comply with policy requirements and will not cause harmful interference.

Dynamic Spectrum Access (DSA) approaches, which propose to opportunistically use underutilized portions of licensed wireless spectrum such as cellular bands, are increasingly being seen as a way to alleviate spectrum scarcity. However, before DSA approaches can be enabled, it is important that we understand the dynamics of spectrum usage in licensed bands. Our focus in this paper is the cellular band. Using a unique dataset collected inside a cellular network operator, we analyze the usage in cellular bands and discuss the implications of our results on enabling DSA in these bands. One of the key aspects of our dataset is its scale – it consists of data collected over three weeks at hundreds of base stations. We dissect this data along different dimensions to characterize if and when spectrum is available, develop models of primary usage and understand the implications of these results on DSA techniques such as sensing.

Abstract—Most existing studies of spectrum usage have been performed by actively sensing the energy levels in specific RF bands including cellular bands. In this paper, we provide a unique, complementary analysis of cellular primary usage by analyzing a dataset collected inside a cellular network operator. One of the key aspects of our dataset is its scale – it consists of data collected over three weeks at hundreds of base stations. We dissect this data along different dimensions to characterize and model primary usage as well as understand its temporal and spatial variations. Our analysis reveals several results that are relevant if Dynamic Spectrum Access (DSA) approaches are to be deployed for cellular frequency bands. For instance, we find that call durations show significant deviations from the oftenused exponential distribution, which makes call-based modeling more complicated. We also show that a random walk process, which does not use call durations, can often be used for modeling the aggregate cell capacity. Furthermore, we highlight some applications of our results to improve secondary usage of licensed spectrum. I.

My research interests lie in the broad area of networked systems, in particular, wireless networking, experimental computer systems, pervasive and mobile computing. I approach networking research problems primarily from a systems perspective, giving emphasis on system design, experimentation, measurement, modeling and performance evaluation. My dissertation research addressed two grand challenges in building next generation broadband wireless access networks – improving capacity and connectivity. In the near future, I envision my research to be useful in providing high speed, reliable and low cost ubiquitous broadband wireless access to users. In this document, I first describe my dissertation research, then discuss other research I have done on dynamic spectrum management, software defined radios and multi-sector antennas, and finally present my future research agenda. Dissertation Research In dense deployments and high traffic scenarios, wireless networks are often interference limited necessitating techniques in capacity improvement. In highly mobile scenarios, clients require good connectivity to wireless infrastructures with fewer hand-offs and low end-to-end delay. My thesis research addressed these challenges in the context of IEEE 802.11 based wireless access networks by proposing network layer and MAC layer solutions that exploit physical layer enhancements such as directional communication and multi-channel support. The first part of my dissertation investigated the use of multiple channels and directional communication to improve

COPYRIGHT 2011 Gaurav S. KasbekarTo my dear family iii Acknowledgments First and foremost, I would like to thank my advisor Prof. Saswati Sarkar for her tremendous help and guidance throughout my PhD. Despite her busy schedule, she spent a large amount of time and effort regularly mentoring me. After I started my PhD research, she pointed me to open research problems that I could work on until I gained the necessary experience to formulate problems on my own. She carefully read multiple drafts of each of my papers and provided detailed comments, due to which I learnt to write papers well. I acquired a sound foundation in mathematics due to my collaboration with her and she helped me to prove several of the results in my thesis. I also got into the good habit of writing mathematical proofs rigorously, since she would

We address the question of optimal trading of bandwidth (service) contracts in wireless spectrum markets, for the primary as well as the secondary spectrum providers in this context. We propose a structured spectrum market and consider two basic types of spectrum contracts that can help attain desired flexibilities and trade-offs in terms of service quality, spectrum usage efficiency and pricing – long-term guaranteed-bandwidth contracts, and short-term opportunisticaccess contracts. A primary provider (seller) and a secondary provider (buyer) creates and maintains a portfolio composed of an appropriate mix of these two types of contracts. The optimal contract trading question in this context amounts to how the spectrum contract portfolio of a seller (buyer) in the spectrum market should be dynamically adjusted so as to maximize return (minimize cost) subject to meeting the bandwidth demands of its own subscribers. In this paper, we formulate the optimal contract trading question as a stochastic optimization problem, and obtain structural properties of the optimal dynamic trading strategy that takes into account the current market prices of the contracts and the provider usage (subscriber demand) process in the decisionmaking. We evaluate and study the optimal dynamic trading strategy numerically, and compare it with a static portfolio optimization strategy where the key trading decision is made in advance, based on the steady-state statistics of the price and usage processes.