Cognitive Radio Scenario Research Articles

Tri-polarized spectrum sensing based on an experimental outdoor-to-indoor cognitive-radio scenario

Compared to classical spatially separated multiple antenna system, cross-polarized co-located antenna systems are an interesting way to reduce equipment size while reducing the inter-antenna correlation. In this paper the spectrum sensing of a Cognitive Radio (CR) system taking advantage of polarization diversity under Rayleigh fading is investigated and compared to an equivalent system using spatial diversity. This analysis is based on a theoretical formulation applied to a real-world scenario. For this purpose, an outdoor-to-indoor measurement campaign at a frequency of 3.5 GHz is realized, where an indoor secondary user senses the signals received from an outdoor primary base station. The signals received at each antenna are first combined and then applied to an energy detector. The theoretical expressions are simulated in the measurement context. The detection probability behavior as a function of distance between the Primary Transmitter (PTx) and the Secondary Terminal (STE) and the inter-antenna correlation effect on the sensing performance are studied.

Distributed Power Allocation for Secondary Users in a Cognitive Radio Scenario

The major contribution of this paper is distributed power allocation for a multi-user multi-channel Cognitive Radio (CR) network which deploys overlay spectrum sharing by the Primary Users (PUs) and Secondary Users (SUs), and Frequency Division Multiplexing Access (FDMA) for the SUs. The transmit power of each SU is constrained by an individual node power budget, the interference threshold on the PU band, as well as the interference caused to the neighboring SUs. Motivated by the non-convex structure of the problem and the need to execute the power allocation distributedly, the problem is cast within a game theoretic frame-work. Pay-off functions for the SUs are formulated to suit the system model, and the Nash Equilibrium for the game is analyzed. Simulation results are provided to validate the mathematical concepts and to evaluate the performance of the proposed distributed power control algorithm in comparison with other relevant schemes.

Entry, Competition, and Regulation in Cognitive Radio Scenarios: A Simple Game Theory Model

Spectrum management based on private commons is argued to be a realistic scenario for cognitive radio deployment within the current mobile market structure. A scenario is proposed where a secondary entrant operator leases spectrum from a primary incumbent operator. The secondary operator innovates incorporating cognitive radio technology, and it competes in quality of service and price against the primary operator in order to provide service to users. We aim to assess which benefit users get from the entry of secondary operators in the market. A game theory‐based model for analyzing both the competition between operators and the subscription decision by users is proposed. We conclude that an entrant operator adopting an innovative technology is better off entering the market, and that a regulatory authority should intervene first allowing the entrant operator to enter the market and then setting a maximum amount of spectrum leased. This regulatory intervention is justified in terms of users utility and social welfare.

Probabilistic greedy pursuit for streaming compressed spectrum sensing

This paper presents a probabilistic greedy pursuit (PGP) algorithm for compressed wide-band spectrum sensing under cognitive radio (CR) scenario. PGP relies on streaming compressed sensing (CS) framework, which differs from traditional CS processing way that only focuses on fixed-length signal's compressive sampling and reconstruction. It utilizes analog-to-information converter (AIC) to perform sub-Nyquist rate signal acquisition at the radio front-end (RF) of CR, the measurement process of which is carefully designed for streaming framework. Since the sparsity of wide-band spectrum is unavailable in practical situation, PGP introduces the probabilistic scheme by dynamically updating support confidence coefficient and utilizes greedy pursuit to perform streaming spectrum estimation, which gains sensing performance promotion progressively. The proposed algorithm enables robust spectrum estimation without the priori sparsity knowledge, and keeps low computational complexity simultaneously, which is more suitable for practical on-line applications. Various simulations and comparisons validate the effectiveness of our approach.

Robust automatic modulation classification and blind equalization: novel cognitive receivers

The automatic modulation classifier (AMC) is an important signal processing component that helps the cognitive radio (CR) better utilize the spectrum. In a typical CR scenario, training sequence or channel knowledge is not available, and hence blind equalizers are widely used. The multipath fading channel not only affects symbol detection performance but also affects the performance of the AMC. In a conventional single input single output blind equalizer, the weights of the equalizer are adapted by minimizing cost functions that are non quadratic (multimodal). Convergence of the blind equalizer to a local minimum affects both symbol detection performance and AMC performance. In a CR scenario, it is preferable to consider the performance of the AMC also while adapting the blind equalizer weights. In this article, we propose novel CR receivers where the performance of the AMC is also considered while adapting the parameters of the blind equalizer. Computer simulations are given to illustrate the concept and yield promising results.

Non-cooperative spectrum access in cognitive radio networks: A game theoretical model

Cognitive radio networks provide the capability to share the wireless channel with licensed (primary) users in an opportunistic manner. Primary users have a license to operate in a certain spectrum band; their access can only be controlled by the primary operator and is not affected by any other unlicensed (secondary) user. On the other hand, secondary users (SUs) have no spectrum license, and they attempt to exploit the spectral gaps left free by primary users. This work studies the spectrum access problem in cognitive radio networks from a game theoretical perspective. The problem is modeled as a non-cooperative spectrum access game where secondary users access simultaneously multiple spectrum bands left available by primary users, optimizing their objective function which takes into account the congestion level observed on the available spectrum bands. As a key innovative feature with respect to existing works, we model accurately the interference between SUs, capturing the effect of spatial reuse. Furthermore, we consider both non-elastic and elastic user traffic, to model real-time as well as data transfer applications. Finally, we consider an alternative formulation of the spectrum access problem, where players use replicator dynamics to adjust their strategies, and we derive convergence conditions to Nash equilibrium points. We demonstrate the existence of the Nash equilibrium, and derive equilibrium flow settings. Finally, we provide numerical results of the proposed spectrum access game in several cognitive radio scenarios, and study the impact of the interference between SUs on the game efficiency. Our results indicate that the congestion cost functions we propose in this paper lead to small gaps between Nash equilibria and optimal solutions in all the considered network scenarios, thus representing a starting point for designing pricing mechanisms so as to obtain a socially optimal use of the network.

Efficient exploration in reinforcement learning-based cognitive radio spectrum sharing

This study introduces two novel approaches, pre-partitioning and weight-driven exploration, to enable an efficient learning process in the context of cognitive radio. Learning efficiency is crucial when applying reinforcement learning to cognitive radio since cognitive radio users will cause a higher level of disturbance in the exploration phase. Careful control of the tradeoff between exploration and exploitation for a learning-enabled cognitive radio in order to efficiently learn from the interactions with a dynamic radio environment is investigated. In the pre-partitioning scheme, the potential action space of cognitive radios is reduced by initially randomly partitioning the spectrum in each cognitive radio. Cognitive radios are therefore able to finish their exploration stage faster than more basic reinforcement learning-based schemes. In the weight-driven exploration scheme, exploitation is merged into exploration by taking into account the knowledge gained in exploration to influence action selection, thereby achieving a more efficient exploration phase. The learning efficiency in a cognitive radio scenario is defined and the learning efficiency of the proposed schemes is investigated. The simulation results show that the exploration of cognitive radio is more efficient by using pre-partitioning and weight-driven exploration and the system performance is improved accordingly.

Spectrally efficient sensing protocol in cognitive relay systems

In this study, the authors consider a cognitive radio scenario and focus on the spectrum efficiency of sensing-transmission protocols for a secondary dual-hop relay system. A straightforward dedicated sensing protocol is first considered as a benchmark, where sensing is performed in dedicated sensing periods at both the source (S) and the relay (R) before their respective transmissions. This, however, leads to a substantial loss in spectrum efficiency for the secondary system. In view of the spectrum efficiency loss in the dedicated sensing protocol, the authors propose an alternative approach, namely simultaneous sensing protocol. In this protocol, sensing is only performed at S, during the period when R transmits to destination (D), by cancelling out the self-interference component that is known a priori. The authors derive the closed-form expression of the average probability of detection for the proposed simultaneous sensing protocol. Furthermore, by deriving the average collision time and average utilisation time for both the dedicated and simultaneous sensing protocols, the authors show that the simultaneous sensing protocol significantly improves the spectrum efficiency for the secondary system and also achieves a higher overall spectrum utilisation of the spectrum band, compared to the dedicated sensing protocol.

Two-stage reinforcement-learning-based cognitive radio with exploration control

This study presents a novel two-stage reinforcement-learning-based algorithm for distributed cognitive radio (CR) spectrum sharing. The traditional reinforcement-learning model is modified in order to be applied in a fully distributed CR scenario. CRs are able to discover the best available resources autonomously by utilising learning, which results in significantly improved performance, while reducing the need for spectrum sensing. Instead of sensing all available spectrum arbitrarily, the scheme is designed to share the spectrum based on an optimal spectrum sharing strategy, which is discovered by the CR agents from their trial-and-error interactions with the wireless communication environment. On the other hand, the inherent exploration against exploitation trade-off seen in reinforcement learning is also examined in the context of CR. A ‘warm-up’ stage is proposed to effectively control the exploration phase of the learning process. A better system performance can be expected by carefully balancing the tradeoff between exploration and exploitation. The benefit of applying a warm-up stage is demonstrated. Comparisons of system performance using different warm-up strategies are also given to illustrate their impact on the spectrum sharing process.

Cooperative strategies of wireless access technologies: A game-theoretic analysis

The wireless Internet has to overcome the problem of spectrum scarcity as the number of mobile equipments could increase even by an order of magnitude in the next decade; the cooperation of mobile devices is foreseeable as a feasible solution to the problems. There exists a large body of literature on opportunistic ad hoc networking including Pelusi et al. (2006) [25], Chen et al. (2006) [26], Hui et al. (2005) [27]; however, the impact of the location of the devices on their access method selection is not yet appropriately dealt with. In this paper, we address this issue based on game-theoretic analyses. The key contribution of our work is threefold. First, we model the access method selection of mobile devices by extending the classical forwarding game with position, mobility, and availability of the devices. Second, we apply the model in game-theoretic analyses to better understand the optimal cooperation strategies in the presence of heterogeneous wireless technologies. We further extend our framework to include uncertainty. Finally, we present the applicability of the model in a cognitive radio scenario where complex structures of parameters are included.

Malicious User Detection in a Cognitive Radio Cooperative Sensing System

Reliable detection of primary users (PUs) is an important task for cognitive radio (CR) systems. Cooperation among a few spectrum sensors has been shown to offer significant gain in the performance of the CR spectrum-sensing system by countering the shadow-fading effects. We consider a parallel fusion network in which the sensors send their sensing information to an access point which makes the final decision regarding presence or absence of the PU signal. It has been shown in the literature that the presence of malicious users sending false sensing data can severely degrade the performance of such a cooperative sensing system. In this paper, we investigate schemes to identify the malicious users based on outlier detection techniques for a cooperative sensing system employing energy detection at the sensors. We take into consideration constraints imposed by the CR scenario such as the lack of information about the primary signal propagation environment and the small size of the sensing data samples. Considering partial information of the PU activity, we propose a novel method to identify the malicious users. We further propose malicious user detection schemes that take into consideration the spatial information of the CR sensors. The performance of the proposed schemes are studied using simulations.

OFDMA Resource Allocation in Wireless Communications

Based on the popular orthogonal frequency division multiplexing (OFDM), frequency division multiple access (OFDMA) has emerged as a primary multi-user multiple access scheme in broadband wireless communication systems. In this paper, recent patents on resource allocation techniques in OFDMA-based wireless systems are overviewed. Specifically, we use single cell single input single output (SISO) as the base model and discuss inventions on OFDMA resource allocation in single cell, multi-cell, multiple input multiple output (MIMO), relay and cognitive radio scenarios. As the new multiple access scheme, OFDMA has many advantages over its predecessor CDMA. These patents demonstrate how to exploit the full potential of OFDMA by efficient subcarrier and power allocation in practical wireless communication systems. Finally, this paper forecasts that resource allocation for cooperative systems, hybrid systems, and cognitive Ad Hoc networks will be future research directions. This overview paper aims to provide valuable insight to OFDMA fundamentals for both system engineers and research scholars. Keywords: Cognitive radio, MIMO, multi-cell, OFDMA, relay, resource allocation

Pilot-Based Synchronization and Equalization in Filter Bank Multicarrier Communications

This paper presents a detailed analysis of synchronization methods based on scattered pilots for filter bank based multicarrier (FBMC) communications, taking into account the interplay of the synchronization, channel estimation, and equalization methods. We show that by applying pilots designed specifically for filter banks, the carrier frequency offset (CFO), fractional time delay (FTD), and channel response can be accurately estimated. Further, a novel joint FTD and channel estimation scheme, based on iterative interference cancelation, permits extending the FTD estimation range well beyond the limit imposed by the pilot separation. The channel parameter estimation and compensation are successfully performed totally in the frequency domain, in a subchannel-wise fashion, which is appealing in spectrally agile and cognitive radio scenarios. The performance evaluation is done in a hypothetical WiMAX scenario in which an FBMC system would substitute OFDM maintaining as much physical layer compatibility as possible.

Throughput analysis of non-persistent carrier sense multiple access combined with time division multiple access and its implication for cognitive radio

This study analyses a cognitive radio scenario based on non-persistent carrier sense multiple access (CSMA) and time division multiple access (TDMA) systems sharing a single-channel wireless network. TDMA users are considered as primary users who can access the channel at any time, and non-persistent CSMA users are considered as secondary users who can share the channel when it is free. New expressions for the individual and aggregate throughput performance of this combined system have been developed, and the system performance is evaluated for a variety of proportions of non-persistent CSMA and TDMA traffic levels. Simulation and analytical results are presented and the ways in which both schemes suffer negative effects as a result of the interaction are shown, primarily caused by increased number of collisions arising from the other scheme.

An executable meta-model of a hierarchical and distributed architecture management for cognitive radio equipments

A cognitive radio (CR) equipment is a radio device that supports the smart facilities offered by future cognitive networks. Even if several categories of equipments exist (terminal, base station, smart PDA, etc.), with their different processing capabilities (and associated cost or power consumption), this means that apart from the usual radio signal processing elements, these equipments have to integrate also a set of new capabilities for the CR support; this implies not only radio adaptation and sensing capabilities. We assert that it is necessary to add some management facilities for that, and we propose here an architecture management to be inserted inside CR equipments named thereafter Hierarchical and Distributed Cognitive Architecture Management (HDCRAM). This approach is based upon a Hierarchical and Distributed Reconfiguration Management (HDReM), which is derived from our previous research on software-defined radio. The HDCRAM extends the HDReM towards CR while adding new management features, in order to support sensing and decision-making facilities. It consists in the combination of one Cognitive Radio Management Unit (CRMU) with each reconfiguration management unit distributed in the equipment. Each of these CRMU is in charge of the capture, the interpretation, and the decision making according to its own goals. In this cognitive radio context, the term “decision” refers to the adaptation of the radio parameters to the equipment environment. This paper details the management functionality and structure of the HDCRAM. Moreover, this architecture has also been modeled with a meta-programming language based on UML. The first goal is to propose a comprehensive specification of the CR management of future CR equipments. Beyond this objective, we have also derived a simulator from the obtained meta-model, which gives the opportunity to specify CR needs and play a wide variety of scenarios in order to validate the CR design. The example of a Blind Standard Recognition CR scenario illustrates the relevance of this approach.

On capacity of cognitive radio networks with average interference power constraints

Cognitive radio (CR) has been considered as a promising technology to improve the spectrum utilization. In this paper we analyze the capacity of a CR network with average received interference power constraints. Under the assumptions of uniform node placements and a simple power control scheme, the maximum transmit power of a target CR transmitter is characterized by its cumulative distribution function (CDF). We study two CR scenarios for future applications. The first scenario is called the CR based central access network, which aims at providing broadband access to CR devices. In the second scenario, the so-called CR assisted virtual multiple-input multiple-output (MIMO) network, CR is used to improve the access capability of a cellular system. The uplink ergodic channel capacities of both scenarios are derived and analyzed with an emphasis on understanding the impact of numbers of primary users and CR users on the capacity. Numerical and simulation results suggest that the CR based central access network is more suitable for less-populated rural areas where a relatively low density of primary receivers is expected; while the CR assisted virtual MIMO network performs better in urban environments with a dense population of mobile CR users.

Statistical resource allocation for multi-band Cognitive Radio systems

A recent development in wireless communications is Cognitive Radio (CR) technology, an innovative design approach which allows the realization of optimal allocation of the scarce radio resources such as the spectrum. Successful resource allocation in CR systems has to overcome the uncertainty of spectrum bands availability as well as the chaotic wireless propagation environment. Previously, most research in resource allocation in CRs has mainly concentrated on the spectrum opportunity discovery aspect while the robust QoS performance problem has remained largely unexplored. In this paper, we jointly consider the power control and spectrum band discovery problems under uncertain CR operative environments. This problem setting is a direct analogy of the portfolio optimization (PO) concept. In PO, once the variance of return is known, then an investor can use the information to find a wealth allocation strategy so as to minimize the investment risk. Similarly, in uncertain CR scenarios, once the variance of a QoS parameter (e.g., throughput) is known, then a power allocation strategy can be obtained leading to reliable communication. The resulting power strategy also marks out the subbands to be used — essentially achieving soft spectrum sensing. In this work, we shall use the concept of portfolio optimization to jointly achieve power control and subband allocation over uncertain CR environments. The limitations of the approaches are investigated through the sensitivity analysis of the solutions obtained. A raw data processing approach will also be given leading to an alternative algorithm for stable data processing. Numerical results are presented to demonstrate the potential of the proposed approaches.

Utilization-Based Modeling and Optimization for Cognitive Radio Networks

The cognitive radio technique promises to manage and allocate the scarce radio spectrum in the highly varying and disparate modern environments. This paper considers a cognitive radio scenario composed of two queues for the primary (licensed) users and cognitive (unlicensed) users. According to the Markov process, the system state equations are derived and an optimization model for the system is proposed. Next, the system performance is evaluated by calculations which show the rationality of our system model. Furthermore, discussions among different parameters for the system are presented based on the experimental results.

Interference-limited resource allocation for cognitive radio in orthogonal frequency-division multiplexing networks

Efficient and fair resource allocation strategies are being extensively studied in current research in order to address the requirements of future wireless applications. A novel resource allocation scheme is developed for orthogonal frequency-division multiplexing (OFDM) networks designed to maximise performance while limiting the received interference at each user. This received interference is in essence used as a fairness metric; moreover, by defining different interference tolerances for different sets of users, the proposed allocation scheme can be exploited in various cognitive radio scenarios. As applied to the scheme, the authors investigate a scenario where two cellular OFDM-based networks operate as primary and secondary systems in the same band, and the secondary system benefits by accessing the unused resources of the primary system if additional capacity is required. The primary system benefits either by charging the secondary system for the use of its resources or by some form of reciprocal arrangement allowing it to use the secondary system's licenced bands in a similar manner, when needed. Numerical results show our interference-limited scheduling approach to achieve excellent levels of efficiency and fairness by allocating resources more intelligently than proportional fair scheduling. A further important contribution is the application of sequential quadratic programming to solve the non-convex optimisation problems which arise in such scenarios.