Dinesh Datla

Parametric Adaptive Spectrum Sensing Framework for Dynamic Spectrum Access Networks

The opportunistic usage of the spectrum must be done without causing any interference to the licensed spectrum users. Conventional non-adaptive wideband spectrum sensing approaches could potentially be inefficient since they generally employ the same scanning resolution, even though the spectrum might contain different types of signals, individually requiring scans with different resolutions. In this paper, we present a novel spectrum sensing framework that adapts its parameters across the spectrum of interest according to the characteristics of its occupancy. We also propose a dynamic scheduling algorithm for spectrum sensing which allocates different time resolutions to different portions of the spectrum. We demonstrate that the proposed algorithm improves the efficiency of spectrum sensing over a non-adaptive approach.

A Spectrum Surveying Framework for Dynamic Spectrum Access Networks

Dynamic spectrum access networks and wireless spectrum policy reforms heavily rely on accurate spectrum utilization statistics, which are obtained via spectrum surveys. In this paper, we propose a generic spectrum-surveying framework that introduces both standardization and automation to this process, as well as enables a distributed approach to spectrum surveying. The proposed framework outlines procedures for the collection, analysis, and modeling of spectrum measurements. Furthermore, we propose two techniques for processing spectrum data without the need for a priori knowledge. In addition, these techniques overcome the challenges associated with spectrum data processing, such as a large dynamic range of signals and the variation of the signal-to-noise ratio across the spectrum. Finally, we present mathematical tools for the analysis and extraction of important spectrum occupancy parameters. The proposed processing techniques have been validated using empirical spectrum measurements collected from the FM, television (TV), cellular, and paging bands. Results show that the primary signals in the FM band can be classified with a miss-detection rate of about 2% at the cost of 50% false-alarm rate, while nearly 100% reliability in classification can be achieved with the other bands. However, the classification accuracy depends on the duration and the range of frequencies over which data are collected, as well as the RF characteristics of the spectrum measurement receiver.

Wireless distributed computing: a survey of research challenges

Recent advancements in radio technology provide great flexibility and enhanced capabilities in executing wireless services. One of these capabilities that can provide significant advantages over traditional approaches is the concept of collaborative computing in wireless networks. With collaborative radio nodes, multiple independent radio nodes operate together to form a wireless distributed computing (WDC) network with significantly increased performance, operating efficiency, and abilities over a single node. WDC exploits wireless connectivity to share processing- intensive tasks among multiple devices. The goals are to reduce per-node and network resource requirements, and enable complex applications not otherwise possible, e.g., image processing in a network of small form factor radio nodes. As discussed in this article, WDC research aims to quantify the benefits of distributed processing over local processing, extend traditional distributed computing (DC) approaches to allow operation in dynamic radio environments, and meet design and implementation challenges unique to WDC with the help of recently available enabling technologies, such as software radios and cognitive radios.

Feasibility of Dynamic Spectrum Access in Underutilized Television Bands

This paper presents the preliminary results from a feasibility study regarding the operation of secondary spectrum users within unused television spectrum. Television spectrum is known within the wireless communications community as being underutilized, making it a prime candidate for dynamic spectrum access. Nevertheless, the quality of this spectrum for enabling secondary transmissions has never been assessed. Two unique scenarios are examined:(i) the possibility of unlicensed devices interfering with digital TV reception, and (ii) the possibility of secondary users experiencing interference when operating within close proximity to television towers. With respect to the former, we investigate the critical operating parameters for developing the technical rules for device operation in bands adjacent to a digital television transmission. Regarding the latter, we examine, via measurement campaign, how non-ideal transmission properties of television broadcasts, including intermodulation and saturation effects, can potentially impair the performance of secondary transmissions.

Wireless distributed computing in cognitive radio networks

Individual cognitive radio nodes in an ad-hoc cognitive radio network (CRN) have to perform complex data processing operations for several purposes, such as situational awareness and cognitive engine (CE) decision making. In an implementation point of view, each cognitive radio (CR) may not have the computational and power resources to perform these tasks by itself. In this paper, wireless distributed computing (WDC) is presented as a technology that enables multiple resource-constrained nodes to collaborate in computing complex tasks in a distributed manner. This approach has several benefits over the traditional approach of local computing, such as reduced energy and power consumption, reduced burden on the resources of individual nodes, and improved robustness. However, the benefits are negated by the communication overhead involved in WDC. This paper demonstrates the application of WDC to CRNs with the help of an example CE processing task. In addition, the paper analyzes the impact of the wireless environment on WDC scalability in homogeneous and heterogeneous environments. The paper also proposes a workload allocation scheme that utilizes a combination of stochastic optimization and decision-tree search approaches. The results show limitations in the scalability of WDC networks, mainly due to the communication overhead involved in sharing raw data pertaining to delegated computational tasks.

Green Communications: A Call for Power Efficient Wireless Systems

Telecommunication usage has skyrocketed in recent years and will continue to grow as developing world reaches to wireless as the communication medium of choice. The telecommunications world is only now addressing the significant environmental impact it is creating as well as the incredible cost on power usage. This realization has led to a push towards Green Communications that strives for improving energy efficiency as well as energy independence of telecommunications. A survey of existing metrics for energy efficiency is discussed with specific adaptations for a communication centric viewpoint. This paper reviews recent energy efficient advances made at specific point within the communications cycle such as components, network operation and topology, and incorporating renewable and alternative energy into base stations. We further survey several holistic approaches that illustrate the dependencies between layers of the communications stack and operation/deployment. These approaches include cross layer design, cognitive radio, and wireless distributed computing.

Power Efficiency in Wireless Network Distributed Computing

Advanced wireless applications such as sensor networks involve a close interaction between the communication and computation processes that deliver the services under stringent power constraints. Wireless network distributed computing (WNDC) is a potential solution to reducing the power consumption per node as well as that of the network. In WNDC, a computational task is executed among a network of collaborative nodes in a distributed manner as against performing the same task on a single node. In addition to providing power savings, WNDC enables power demand–supply matching that allows for system operation under a constrained power supply such as solar power. This paper presents fundamental power efficiency analysis of WNDC. The conditions for achieving power demand– supply matching and positive network power savings under power and computational latency constraints are derived. The results show the impact of non–linearity in the computational system characteristics and the communication overhead on the power savings.

Distributed Power Allocations in Heterogeneous Networks With Dual Connectivity Using Backhaul State Information

Long Term Evolution (LTE) release 12 proposes the use of dual connectivity in heterogeneous cellular networks, where a user equipment (UE) maintains parallel connections to a macrocell base station and to a low-tier node such as a picocell base station or relay. In this paper, we propose distributed multi-objective power control where each UE independently adapts its transmit power on its dual connections, where the uplinks could be of unequal bandwidth and have non-ideal backhaul links. In the proposed optimization, the UEs dynamically switch between data rate maximization and transmit power minimization as the backhaul load varies. To address the coupling between interference and the backhaul load, we propose a low-overhead convergence mechanism which does not require explicit coordination between UEs and also derive a closed-form expression of the transmit power levels at equilibrium. Simulation results show that our scheme achieves higher aggregate end-to-end data rate and significant power saving in comparison to a scheme that employs a greedy algorithm and a scheme that employs only waterfilling.

The Impact of Channel Variations on Wireless Distributed Computing Networks

Wireless distributed computing has several unique problems compared with currently well investigated wireless sensor networks. These problems include the impact of channel variation on power allocation, different traffic pattern with higher utilization, and more restricted delay constraints. This paper investigates the impact of communication channel condition on the average execution time of the computing task within wireless distributed computing networks (WDCN). It has been found that the delay performance of wireless distributed computing is influenced by both the average channel condition and the variation of channels. In addition, the impact of channel heterogeneity is also investigated to show the possibility of the optimal workload distribution for energy saving and robustness. Finally, a workload distribution approach combined with a power allocation scheme exploiting the spatial heterogeneity of the channel condition is proposed to balance energy efficiency and robustness.

Interference Effects of Non-Ideal Dynamic Spectrum Access on Primary and Secondary User Capacities

Dynamic spectrum access (DSA) technology can improve the spectrum utilization significantly and is the key solution to the spectrum scarcity problem. In a typical DSA scenario, the secondary user (SU) is required to co-exist with the primary user (PU) in a non-interfering manner. However, the SUs spectrum sensing limitations can result in erroneous secondary transmissions that can affect the PUs capacity. In this paper, we model the interference caused by the SU to the PU and simulate the resulting capacity loss experienced by the PU. The trends in the PU and SU capacities that occur with variation in the system parameters such as transmit SNR, PU - SU spatial separation and the spectrum sensing time have been discussed. The results presented in this paper show that the capacity loss of the PU as well as the SU due to DSA interference is insignificant when limits are placed on the SU system parameters. Furthermore, the maximum effective throughput that can be achieved by the SU under such limited operation is also computed.