Statistical Interference Modeling and Coexistence Strategies in Cognitive Wireless Networks

STATISTICAL INTERFERENCE MODELING AND COEXISTENCE STRATEGIES IN COGNITIVE WIRELESS NETWORKS Alireza Babaei, PhD George Mason University, 2009 Dissertation Director: Dr. Bijan Jabbari Cognitive radio is a novel approach for better utilization of the scarce, already packed but highly underutilized radio spectrum. To this end, environment-aware unlicensed secondary wireless devices are envisioned to share the spectrum with the primary licensed network, provided that their operation does not impose unmanageable interference on the primary nodes. To achieve this coexistence goal, interference modeling is of great significance. Interference, in general, has a stochastic nature not only due to randomness in the propagation channel, but also due to the random geographic dispersion of nodes. A statistical representation for interference, in which the power levels of the secondary nodes influence the parameters of the model, is, thus, of considerable interest in analysis and design of cognitive wireless network. Stochastic geometry and spatial point processes are used for modeling the coexisting primary and secondary networks. In particular, we model these networks using spatial bivariate Poisson processes. We obtain statistical properties of the distances in these processes and use them for modeling the interference from secondary network on the primary nodes. We first consider an approximate Gaussian model for interference assuming that Central Limit Theorem (C.L.T) can be applied. We, then, show that a more accurate model for interference is the sum of a Normal and a Log-normal random variables. The power levels of secondary nodes can be adjusted to obtain desirable values for the parameters in both of these models. Having this characterization of interference, we propose power control strategies for the secondary network which assure the satisfaction of interference constraint at the primary nodes. We show that these strategies are very easy to implement with little coordination requirement. Nodes either need to know where they are located in the sequence of nodes ordered according to their Euclidean distance to a primary node or need no location information, based on which strategy is being used. Given that secondary nodes have imposed power control strategies to coexist with the primary nodes, we find the lower bound of achievable throughput for the secondary nodes. We use the statistical properties of distances between secondary nodes and find an upper bound for the interference of secondary network on an arbitrary secondary node and thereby a lower bound for its throughput. We show that the approach is applicable to finding the throughput in a general power-constrained random network. Chapter 1: Introduction and Motivation 1.1 Spectrum Scarcity or Shortage of Tolerance? Today, we are witnessing an unprecedented growth in demand for wireless technology. Several novel applications requiring high bandwidth are increasing the demand for radio spectrum. The radio frequencies, once perceived as an abundant resource, has turned into a seemingly diminishing commodity. A brief look at the domestic and international frequency allocation charts may lead to the conclusion that we are actually approaching the capacity of radio spectrum. As of late, the trend to increase spectral efficiency, has been at the system level. This means that, for an allocated frequency band to a particular system, the communications engineers try to take the most out of it, e.g., by closing the gap to Shannon capacity as much as possible. Despite tremendous advances in physical layer techniques for more efficient use of radio spectrum, the problem still remains intact: how can the emerging wireless applications be integrated in the current overly crowded radio spectrum? This necessitates, as a sine qua non, a new paradigm and a fundamental revision in approaching the spectrum scarcity problem. According to the Federal Communication Commission (FCC), at a given geographic location, spectrum remains idle for a large portion of time [1]. This brings the following questions: 1) Is the problem really the physical shortage of spectrum, or the outdated spectrum policies that prevent the coexistence? and 2) Can the efficiency of spectrum access be increased by allowing several systems coexist in the same frequency band? In the traditional divide and set aside approach [2], service providers are granted blocks of spectrum along with licenses with which they can have exclusive access to the spectrum. 1 When licensees are not transmitting, the spectrum remains idle. These policies were devised considering the 1920’s technology [3]. Current technology seems to be mature enough to allow spectrum sharing and coexistence among multiple systems. This, of course, requires more tolerance and altruism for a side-by-side coexistence. On the other hand, strict spectrum policies are required to resolve possible conflicts of interest among systems. 1.2 Dynamic Spectrum Access and Cognitive Radios The inefficiency of current static spectrum utilization is reminiscent of the inefficiency of static TDMA for bursty traffic, or in general, the inefficiency of static versus dynamic techniques. A variety of ideas have been proposed to bring about the required spectrum reform and improve the efficiency of its usage, which are all categorized under the general term Dynamic Spectrum Access (DSA) [4]. In this dissertation, we consider a hierarchical model. This model consists of two classes of spectrum users called primary and secondary. The first class, the primary users, are the more favored ones since they possess the license, and therefore the right to use the spectrum without any restriction and when and where they need it. On the other hand, the spectrum is open for the use of secondary unlicensed users, as long as their interference perceived by a primary user is less than some threshold. That is required so that their presence goes unnoticed for the primary users. This responsibility to be vigilant and have an open eye on their operation to limit their interference to the primary users, requires that secondary nodes to be more intelligent and cognitive compared to the conventional wireless devices. In parallel to this recognition, new ideas have been proposed for an intelligent device called Cognitive Radio (CR)[5]. The idea is that CRs have the capability of learning from their surrounding environment and adapting to the statistical variations of the input stimuli. In other words, these radios basically mimic the learning process of human brain. The concept of CR is an extension of the original idea of Software Defined Radio (SDR) [6]. A basic definition of SDR is: a radio in which some or all of the physical layer functions 2 are software defined [7]. CRs can be considered SDRs equipped with artificial intelligence, which make them capable of sensing and reacting to their environment. Various methods have been proposed to employ this cognition capability and make the coexistence possible, which seek to underlay, overlay or interweave the secondary users’ signals with those of the primary users [8]. In the underlay approach, concurrent primary and secondary transmissions are allowed, while power constraints are imposed on the secondary users so that their aggregate interference is below the noise floor of primary users [9]. An example is UWB system where signals with very high bandwidth and very low power spectral density are used. The low power spectral density tends to minimize the interference to primary users. In the overlay scenario, the secondary nodes can decode the primary message and use techniques like dirty paper coding [10] or employ cooperative methods to cancel interference at both primary and secondary nodes. Reference [11] considers a two-sender two-receiver interference channel model, in which sender 2 obtains the encoded message from user 1 in a causal or noncausal manner. Achievable rate regions are found by using ideas from Gel’fand and Pinsker’s coding scheme [12]. Reference [13] discusses that cooperation between secondary nodes for transmission of their own data or cooperative transmission of primary traffic (cognitive relaying) can greatly benefit the implementation of cognitive radio. In the interweave approach, secondary nodes try to detect void space-time-frequency holes and exploit them for their own transmission. Opportunistic Spectrum Access (OSA) is an alternative name used for this method. In [14], a two-switch model is developed that captures the spectral activity estimates at the cognitive transmitter and receiver. Upper and lower bounds are obtained for the capacity of the cognitive radio channel. 1.3 Interference: The Achilles’ Heel In this dissertation, we are mostly concerned with the underlay approach. On the premise that they do not harmfully interfere with their primary counterparts, secondary nodes