Shamik Sengupta

An economic framework for dynamic spectrum access and service pricing

The concept of dynamic spectrum access will allow the radio spectrum to be traded in a market like scenario allowing wireless service providers (WSPs) to lease chunks of spectrum on a short-term basis. Such market mechanisms will lead to competition among WSPs where they not only compete to acquire spectrum but also attract and retain users. Currently, there is little understanding on how such a dynamic trading system will operate so as to make the system feasible under economic terms. In this paper, we propose an economic framework that can be used to guide i) the dynamic spectrum allocation process and ii) the service pricing mechanisms that the providers can use. We propose a knapsack based auction model that dynamically allocates spectrum to the WSPs such that revenue and spectrum usage are maximized. We borrow techniques from game theory to capture the conflict of interest between WSPs and end users. A dynamic pricing strategy for the providers is also proposed. We show that even in a greedy and non-cooperative behavioral game model, it is in the best interest of the WSPs to adhere to a price and channel threshold which is a direct consequence of price equilibrium. Through simulation results, we show that the proposed auction model entices WSPs to participate in the auction, makes optimal use of the spectrum, and avoids collusion among WSPs. We demonstrate how pricing can be used as an effective tool for providing incentives to the WSPs to upgrade their network resources and offer better services.

An Economic Framework for Spectrum Allocation and Service Pricing with Competitive Wireless Service Providers

In the future, we can expect to see more dynamic service offerings and profiles, as users move from long-term service provider agreements to more opportunistic service models. Moreover, when the radio spectrum is itself traded in a market- based scenario, wireless service providers (WSPs) will likely require new strategies to deploy services, define service profiles, and price them. Currently, there is little understanding on how such a dynamic trading system will operate so as to make the system feasible under economic terms. From an economic point of view, we analyze two main components of this overall trading system: (i) spectrum allocation to WSPs and (ii) interaction of end users with the WSPs. For this two-tier trading system, we present a winner determining sealed-bid knapsack auction mechanism that dynamically allocates spectrum to the WSPs based on their bids. We propose a dynamic pricing strategy based on game theory to capture the conflict of interest between WSPs and end users, both of whom try to maximize their respective net utilities. We show that even in such a greedy and non-cooperative behavioral game model, it is in the best interest of the WSPs to adhere to a price threshold which is a consequence of a price equilibrium in an oligopoly situation. Through simulation results, we show that the proposed auction entices the WSPs to participate in the auction, makes optimal use of the common spectrum pool, and avoids collusion among WSPs. Moreover, numerical results demonstrate how pricing can be used as an effective tool for providing incentives to the WSPs to upgrade their network resources and offer better services.

A Game Theoretic Framework for Power Control in Wireless Sensor Networks

In infrastructure-less sensor networks, efficient usage of energy is very critical because of the limited energy available to the sensor nodes. Among various phenomena that consume energy, radio communication is by far the most demanding one. One of the effective ways to limit unnecessary energy loss is to control the power at which the nodes transmit signals. In this paper, we apply game theory to solve the power control problem in a CDMA-based distributed sensor network. We formulate a noncooperative game under incomplete information and study the existence of Nash equilibrium. With the help of this equilibrium, we devise a distributed algorithm for optimal power control and prove that the system is power stable only if the nodes comply with certain transmit power thresholds. We show that even in a noncooperative scenario, it is in the best interest of the nodes to comply with these thresholds. The power level at which a node should transmit, to maximize its utility, is evaluated. Moreover, we compare the utilities when the nodes are allowed to transmit with discrete and continuous power levels; the performance with discrete levels is upper bounded by the continuous case. We define a distortion metric that gives a quantitative measure of the goodness of having finite power levels and also find those levels that minimize the distortion. Numerical results demonstrate that the proposed algorithm achieves the best possible payoff/utility for the sensor nodes even by consuming less power.

Improving Quality of VoIP Streams over WiMax

Real-time services such as VoIP are becoming popular and are major revenue earners for network service providers. These services are no longer confined to the wired domain and are being extended over wireless networks. Although some of the existing wireless technologies can support some low-bandwidth applications, the bandwidth demands of many multimedia applications exceed the capacity of these technologies. The IEEE 802.16-based WiMax promises to be one of the wireless access technologies capable of supporting very high bandwidth applications. In this paper, we exploit the rich set of flexible features offered at the medium access control (MAC) layer of WiMax for the construction and transmission of MAC protocol data units (MPDUs) for supporting multiple VoIP streams. We study the quality of VoIP calls, usually given by R-score, with respect to the delay and loss of packets. We observe that loss is more sensitive than delay; hence, we compromise the delay performance within acceptable limits in order to achieve a lower packet loss rate. Through a combination of techniques like forward error correction, automatic repeat request, MPDU aggregation, and minislot allocation, we strike a balance between the desired delay and loss. Simulation experiments are conducted to test the performance of the proposed mechanisms. We assume a three-state Markovian channel model and study the performance with and without retransmissions. We show that the feedback-based technique coupled with retransmissions, aggregation, and variable length MPDUs are effective and increase the R-score and mean opinion score by about 40 percent.

Open research issues in multi-hop cognitive radio networks

Cognitive radio networks hold the key to achieving better radio bandwidth utilization and improving the quality of wireless applications. The next step in this fast emerging paradigm is the multi-hop cognitive radio network. Well designed multi-hop cognitive radio networks can provide high bandwidth efficiency by using dynamic spectrum access technologies as well as provide extended coverage and ubiquitous connectivity for the wireless end users. However, the special features of multi-hop cognitive radio networks also raise several unique design challenges. In this article, we survey these unique challenges and open research issues in the design of multi-hop cognitive radio networks as well as discuss potential approaches to address these challenges. This article specifically focuses on the medium access control (MAC) and network layers of the multi-hop cognitive radio protocol stack. Issues considered include efficient spectrum sharing, optimal relay node selection, interference mitigation, end-to-end delay, etc.

A Game Theoretic Framework for Distributed Self-Coexistence Among IEEE 802.22 Networks

The cognitive radio based IEEE 802.22 wireless regional area network (WRAN) is designed to operate in the under-utilized TV bands by detecting and avoiding primary TV transmission bands in a timely manner. Such networks, deployed by competing wireless service providers, would have to self-coexist by accessing different parts of the available spectrum in a distributed manner. Obviously, the goal of every network is to acquire a clear spectrum chunk free of interference from other IEEE 802.22 networks so as to satisfy the QoS of the services delivered to the end-users. In this paper, we study the distributed WRAN self-coexistence problem from a minority game theoretic perspective. We model the spectrum band switching game where the networks try to minimize their cost in finding a clear band. We propose a mixed strategy that the competing networks must adhere to in order to achieve the Nash equilibrium. Simulation experiments have also been conducted and results corroborate with the theoretical analysis.

Review: Vulnerabilities in cognitive radio networks: A survey

Cognitive radio networks are envisioned to drive the next generation wireless networks that can dynamically optimize spectrum use. However, the deployment of such networks is hindered by the vulnerabilities that these networks are exposed to. Securing communications while exploiting the flexibilities offered by cognitive radios still remains a daunting challenge. In this survey, we put forward the security concerns and the vulnerabilities that threaten to plague the deployment of cognitive radio networks. We classify various types of vulnerabilities and provide an overview of the research challenges. We also discuss the various techniques that have been devised and analyze the research developments accomplished in this area. Finally, we discuss the open research challenges that must be addressed if cognitive radio networks were to become a commercially viable technology.

Designing auction mechanisms for dynamic spectrum access

With the increasing demands for radio spectrum, techniques are being explored that would allow dynamic access of spectrum bands that are under-utilized. In this regard, a new paradigm called dynamic spectrum access is being investigated where wireless service providers (WSPs) would dynamically seek more spectrum from the under-utilized licensed bands when and where they need without interfering with the primary users. Currently, there is little understanding on how such a dynamic allocation will operate so as to make the system feasible under economic terms. In this paper, we consider the dynamic spectrum allocation process where multiple WSPs (bidders) compete to acquire necessary spectrum band from a common pool of spectrum. We use auction theory to analyze the allocation process when the demand from WSPs exceeds the available spectrum. We investigate various auction mechanisms under different spectrum allocation constraints to find WSPs’ bidding strategies and revenue generated by spectrum owner. We show that sequential bidding of bands provides better result than the concurrent bidding when WSPs are constrained to at most single unit allocation. On the other hand, when the bidders request for multiple units, (i.e., they are not restricted by allocation constraints) synchronous auction mechanism proves to be beneficial than asynchronous auctions.

Feedback-based real-time streaming over WiMax

The IEEE 802.16 standard (commonly known as WiMax) has emerged as one of the strongest contenders for broadband wireless access technology. At the same time, with the steady growth of real-time services such as voice over IP and video on demand, supporting delay sensitive streaming data over WiMax is becoming crucial. In this article we use commonly used techniques such as forward error correction (FEC) and automatic repeat request (ARQ) to support streaming services over WiMax without violating what has already been standardized. In particular, we look at the flexible features provided by media access control (MAC) layer of WiMax and exploit them for providing better streaming performance. We use the channel state information to dynamically construct the MAC packet data units. The sizes of these units are thusly determined such that the packet dropping probability is minimized without compromising the goodput. The simulation results presented show the performance enhancements of the proposed ARQ-enabled adaptive algorithm for streaming data

Competitive Spectrum Trading in Dynamic Spectrum Access Markets: A Price War

The concept of dynamic spectrum access (DSA) enables the licensed spectrum to be traded in an open market where the unlicensed users can freely buy and use the available licensed spectrum bands. However, like in the other traditional commodity markets, spectrum trading is inevitably accompanied by various competitions and challenges. In this paper, we study an important business competition activity - price war in the DSA market. A non-cooperative pricing game is formulated to model the contention among multiple wireless spectrum providers for higher market share and revenues. We calculate the Pareto optimal pricing strategies for all providers and analyze the motivations behind the price war. The potential responses to the price war are in-depth discussed. Numerical results demonstrate the efficiency of the Pareto optimal strategy for the game and the impact of the price war to all participants.