Evaluation of Overlay/underlay Waveform via SD-SMSE Framework for Enhancing Spectrum Efficiency

Recent studies have suggested that spectrum congestion is mainly due to the inefficient use of spectrum rather than its unavailability. Dynamic Spectrum Access (DSA) and Cognitive Radio (CR) are two terminologies which are used in the context of improved spectrum efficiency and usage. The DSA concept has been around for quite some time while the advent of CR has created a paradigm shift in wireless communications and instigated a change in FCC policy towards spectrum regulations. DSA can be broadly categorized as using a 1) Dynamic Exclusive Use Model, 2) Spectrum Commons or Open sharing model or 3) Hierarchical Access model. The hierarchical access model envisions primary licensed bands, to be opened up for secondary users, while inducing a minimum acceptable interference to primary users. Spectrum overlay and spectrum underlay technologies fall within the hierarchical model, and allow primary and secondary users to coexist while improving spectrum efficiency. Spectrum overlay in conjunction with the present CR model considers only the unused (white) spectral regions while in spectrum underlay the underused (gray) spectral regions are utilized. The underlay approach is similar to ultra wide band (UWB) and spread spectrum (SS) techniques utilize much wider spectrum and operate below the noise floor of primary users. Software defined radio (SDR) is considered a key CR enabling technology. Spectrally modulated, Spectrally encoded (SMSE) multi-carrier signals such as Orthogonal Frequency Domain Multiplexing (OFDM) and Multi-carrier Code Division Multiple Access (MCCDMA) are hailed as candidate CR waveforms. The SMSE structure supports and is well-suited for SDR based CR applications. This work began by developing a general soft decision (SD) CR framework, based on a previously developed SMSE framework that combines benefits of both the overlay and underlay techniques to improve spectrum efficiency and maximizing the channel capacity. The resultant SD-SMSE framework provides a user with considerable flexibility to choose overlay, underlay or hybrid overlay/underlay waveform depending on the scenario, situation or need. Overlay/Underlay SD-SMSE framework flexibility is demonstrated by applying it to a family of SMSE modulated signals such as OFDM, MCCDMA, Carrier Interferometry (CI) MCCDMA and Transform Domain Communication System (TDCS). Based on simulation results, a performance analysis of Overlay, Underlay and hybrid Overlay/Underlay waveforms are presented. Finally, the benefits of combining overlay/underlay techniques to improve spectrum efficiency and maximize channel capacity are addressed

Qiu, R. et al. A Unified Multi-Functional Dynamic Spectrum Access Framework: Tutorial, Theory and Multi-GHz Wideband Testbed. Sensors 2009, 9, 6530–6603

We found that the affiliation of author Vasu Chakravarthy was incorrect in our paper published in Sensors recently

A Unified Multi-Functional Dynamic Spectrum Access Framework: Tutorial, Theory and Multi-GHz Wideband Testbed

Dynamic spectrum access is a must-have ingredient for future sensors that are ideally cognitive. The goal of this paper is a tutorial treatment of wideband cognitive radio and radar—a convergence of (1) algorithms survey, (2) hardware platforms survey, (3) challenges for multi-function (radar/communications) multi-GHz front end, (4) compressed sensing for multi-GHz waveforms—revolutionary A/D, (5) machine learning for cognitive radio/radar, (6) quickest detection, and (7) overlay/underlay cognitive radio waveforms. One focus of this paper is to address the multi-GHz front end, which is the challenge for the next-generation cognitive sensors. The unifying theme of this paper is to spell out the convergence for cognitive radio, radar, and anti-jamming. Moore’s law drives the system functions into digital parts. From a system viewpoint, this paper gives the first comprehensive treatment for the functions and the challenges of this multi-function (wideband) system. This paper brings together the inter-disciplinary knowledge

Classification of wireless adhoc networks through misbehavior analysis

We consider the problem of classifying wireless adhoc networks through active injection of waveforms. We look at energy-efficient wireless networks following power control multiple access schemes and consider two types of classification. Class 1 network nodes optimize their own energy consumption and the network can be modeled as a non-cooperative game operating at Nash equilibrium power values. Class 2 network nodes cooperate to minimize joint energy consumption. Once a network has been classified appropriately, it becomes easier to understand its vulnerabilities. We examine the vulnerability of both classes of networks by formulating a model for energy misbehavior by waveform injection by misbehaving nodes. Misbehaving nodes optimally increase interference at good nodes to decrease their own energy consumption while increasing energy consumption at good nodes

Sensing and Transmission in Probabilistically Interference-Limited Cognitive Radio Systems

In this paper, we provide a fundamental channel model to characterize the interference effect inherent in cognitive radio systems. Mutual information rates of our proposed probabilistic block interference channels for both primary and secondary users are derived without assuming that receivers have knowledge on channel interference states. Novel constrained optimization problems are then put forward with a constraint on the performance loss margin tolerated by the primary user. Furthermore, we investigate some special cases where conditions are provided to justify the optimality of adopting Neyman-Pearson rule. Also presented are some scenarios in which randomized decision without using sensing measurement is needed to balance the rateloss for PU and throughput gain for SD. © 2011 IEEE

CSI usage over parallel fading channels under Jamming attacks: A game theory study

Consider a parallel channel with M independent flat-fading subchannels. There exists a smart jammer which has possession of a copy of perfect channel state information (CSI) measured and sent back by a receiver to its transmitter. Under this model, a class of two-person zero-sum games is investigated where either achievable mutual information rate or Chernoff bound is taken as the underlying pay-off function with the strategy space of each player determined by respective power control and hopping functions. More specifically, we have tackled and answered the following three fundamental questions. The first one is about whether the transmitter and jammer should hop or fully use all degrees of freedom over the entire parallel channels given the full CSI available to both of them, i.e. to hop or not to hop. The second question is about the impact of sending back CSI on system performance considering that the smart jammer can exploit CSI to further enhance its interference effects, i.e. to feedback or not to feedback. The last question is about whether the amount of feedback information can be reduced given the mutual restrictions between transmitter and jammer, i.e. when to feedback and when not to. © 2012 IEEE

A fully polynomial approximation algorithm for collaborative relaying in sensor networks under finite rate constraints

We take an algorithmic approach to a well-known communication channel problem and develop several algorithms for solving it. Specifically, we develop power control algorithms for sensor networks with collaborative relaying under bandwidth constraints, via quantization of finite rate (bandwidth limited) feedback channels. We first consider the power allocation problem under collaborative relaying where the tradeoff between minimizing ones own energy expenditure and the energy for relaying is considered under the constraints of packet outage probability and bandwidth constrained (finite rate) feedback. Then we develop bandwidth constrained quantization algorithms (due to the finite rate feedback) that seek the optimal way of quantizing channel quality and power values in order to minimize the total average transmission power and satisfy the given probability of outage. We develop two kinds of quantization protocols and associated quantization algorithms. For separate source-relay quantization, we reduce the problem to the well-known k-median problem [1] on line graphs and show a a simple O((KJ)2 N) polynomial time algorithm, where log2 KJ is the quantization bandwidth and N is the size of the discretized parameter space. For joint quantization, we first develop a simple 2-factor approximation of complexity O(KJN + N log N). Then, for ε \u3e 0, we develop a fully polynomial approximation scheme (FPAS) that approximates the optimal quantization cost to within an 1 + ε-factor. The running time of the FPAS is polynomial in 1/ε, size of the input N and also In F, where F is the maximum available transmit power. © Springer-Verlag Berlin Heidelberg 2007

Approximation algorithms for minimum energy transmission scheduling in rate and duty-cycle constrained wireless networks

We consider a constrained energy optimization called Minimum Energy Scheduling Problem (MESP) for a wireless network of N users transmitting over M time slots, where the constraints arise because of interference between wireless nodes that limits their transmission rates along with load and duty-cycle (onoff) restrictions. Since traditional optimization methods using Lagrange multipliers do not work well and are computationally expensive given the nonconvex constraints, we consider approximation schemes for finding the optimal (minimum energy) transmission schedule by discretizing power levels over the interference channel. First, we show the toughness of approximating MESP for an arbitrary number of users N even with a fixed M. For any T, we demonstrate that there does not exist any (r,r)-bicriteria approximation for this MESP, unless P=NP. Conversely, we show that there exist good approximations for MESP with given N users transmitting over an arbitrary number of M time slots by developing fully polynomial (1,1+\epsilon) approximation schemes (FPAS). For any epsilon, we develop an algorithm for computing the optimal number of discrete power levels per time slot (O(1epsilon)), and use this to design a (1, 1+\epsilon)-FPAS that consumes no more energy than the optimal while violating each rate constraint by at most a 1+epsilon-factor. For wireless networks with low-cost transmitters, where nodes are restricted to transmitting at a fixed power over active time slots, we develop a two-factor approximation for finding the optimal fixed transmission power value Popt that results in the minimum energy schedule. © 2009 IEEE