Primary User Emulation Detection Algorithm Based on Distributed Sensor Networks

In this paper, we propose a novel primary user emulation (PUE) detection approach which employs a distributed sensor network, where each sensor node operates as an independent PUE detector. Distributed nodes collaborate in order to obtain the final detection results for the whole network. A voting algorithm is used to improve the performance of energy detection, while the classification is conducted by the nearest node in order to improve the efficiency of the detector. As a result of voting, if a potential primary user exists, then the features of the unknown user is compared with entries from the database in order to obtain a solid detection match. An artificial neural network (ANN) is used for the classification of an unknown user. To assess the accuracy of the detection result, we implement a reliability check at the output of ANN. The proposed algorithm is validated via computer simulations as well as by experimental hardware implementations using the Universal Software Radio Peripheral (USRP) software-defined radio (SDR) platform. The experiment results show that the distributed network detector detects the PUE 180–200%, depending on the number of primary users, faster than single node detector.     

A framework for statistical wireless spectrum occupancy modeling

In this paper, we propose a novel spectrum occupancy model designed to generate accurate temporal and frequency behavior of various wireless transmissions. Our proposed work builds upon existing concepts in open literature in order to develop a more accurate time-varying spectrum occupancy model. This model can be employed by wireless researchers for evaluating new wireless communication and networking algorithms and techniques designed to perform dynamic spectrum access (DSA). Using statistical characteristics extracted from actual radio frequency measurements, first- and second-order parameters are employed in a statistical spectrum occupancy model based on a combination of several different probability density functions (PDFs) defining various features of a specific spectrum band with several concurrent transmissions. To assess the accuracy of the model, the output characteristics of the proposed spectrum occupancy model are compared with realtime radio frequency measurements in the television and paging bands.     

Efficient spectrum utilization via cross-layer optimization in distributed cognitive radio networks

In this paper, we propose a novel spectrum allocation approach for distributed cognitive radio networks. Cognitive radio systems are capable of sensing the prevailing environmental conditions and automatically adapting its operating parameters in order to enhance system and network performance. Using this technology, our proposed approach optimizes each individual wireless device and its single-hop communication links using the partial operating parameter and environmental information from adjacent devices within the wireless network. Assuming stationary wireless nodes, all wireless communication links employ non-contiguous orthogonal frequency division multiplexing (NC-OFDM) in order to enable dynamic spectrum access (DSA). The proposed approach will attempt to simultaneously minimize the bit error rate, minimize out-of-band (OOB) interference, and maximize overall throughput using a multi-objective fitness function. Without loss in generality, genetic algorithms are employed to perform the actual optimization. Several assisting processes have also been devised to make the approach more efficient and robust. Such procedure is able to reduce BER by an order of magnitude.     

Bit loading with BER-constraint for multicarrier systems

We present discrete adaptive bit loading algorithms for multicarrier systems with uniform (nonadaptive) power allocation operating in a frequency selective fading environment. The algorithms try to maximize the overall throughput of the system while guaranteeing that the mean bit error rate (BER) remains below a prescribed threshold. We also study the impact of imperfect subcarrier signal-to-noise ratio information on throughput performance. Results show that the proposed algorithms have approximately the same throughput and mean BER as the optimal allocation while having a significantly lower computational complexity relative to other algorithms with near-optimal allocations. Moreover, when compared with algorithms that employ approximations to water filling, the computational complexity is comparable while the overall throughput is closer to the optimum.     

Population Adaptation for Genetic Algorithm-based Cognitive Radios

Genetic algorithms are best suited for optimization problems involving large search spaces. The problem space encountered when optimizing the transmission parameters of an agile or cognitive radio for a given wireless environment and set of performance objectives can become prohibitively large due to the high number of parameters and their many possible values. Recent research has demonstrated that genetic algorithms are a viable implementation technique for cognitive radio engines. However, the time required for the genetic algorithms to come to a solution substantially increases as the system complexity grows. In this paper, we present a population adaptation technique for genetic algorithms that takes advantage of the information from previous cognition cycles in order to reduce the time required to reach an optimal decision. Our simulation results demonstrate that the amount of information from the previous cognition cycle can be determined from the environmental variation factor, which represents the amount of change in the environment parameters since the previous cognition cycle.

Implementation and analysis of spectral subtraction in deterministic wide‐band anti‐jamming scenarios

In this paper, we propose an approach for mitigating deterministic and partially deterministic jamming signals from the received signal space, thus yielding recoverable signal vectors at a target receiver. Aimed at friendly or self‐jamming environments, where enemy communication jamming is paramount. The proposed approach employs a concept called spectral subtraction, where one or more known signals can be removed from the received signal space via the subtraction of their spectral characteristics from the received composite signal. Although spectral subtraction is used in a variety of speech communication scenarios, it has not been extensively employed in wireless applications because of several practical challenges, such as achieving both sufficient time alignment and accurate waveform characterization of the signal to be removed. In order to assess these challenges, as well as analyze the potential benefits of the proposed approach, validation was performed using actual over‐the‐air experimentation using software‐defined radio technology. The feasibility study of the proposed approach for achieving sufficient signal removal was examined for a constrained operating scenario, and experimental results show that spectral subtraction can be achieved in a physical transmission environment. Although physical simulations were limited, they provide baseline results for a previously untested method of jammer suppression. Copyright © 2016 John Wiley & Sons, Ltd.     

On uplink CDMA cell capacity: mutual coupling and scattering effects on beamforming

It has been shown that code-division multiple-access (CDMA) systems that employ digital beamforming and base station antenna arrays have the potential to increase capacity significantly. Therefore, accurate performance prediction of such systems is important. We propose to take the electromagnetic behavior of the base station antenna array into account, as well as its impact on wireless channel propagation. Specifically, the wideband channel introduces scattering, while the mobile environment causes Doppler fading, which in turn degrades power controllability. We develop a more accurate performance analysis of antenna arrays, where the performance degradation in digital beamforming, due to the combination of mutual coupling, scatter and imperfect power control, and its impact on uplink CDMA system capacity is quantified. A Rayleigh fading amplitude with varying angle-of-arrival spread is assumed, and maximum signal-to-noise ratio beamforming weights are used. These weights are further correlated with mutual coupling at the base station array. Despite the degradation due to the combination of mutual coupling, scattering, and imperfect power control, significant capacity increases are possible.     

Loading Algorithm for Multicarrier Spatial Diversity Systems with Antenna Selection

In this paper, a novel loading algorithm consisting of four variants is proposed for a multicarrier transceiver employing multiple antennas configured for spatial diversity. The primary objective of the proposed algorithm is to increase the overall throughput while ensuring the mean bit error rate (BER) is below a specified limit. To achieve this, spatial diversity is employed to improve the subcarrier signal-to-noise ratio (SNR) values. Simultaneously, (uniform or non-uniform) bit allocation, which is a function of subcarrier SNR, is performed to increase throughput. To reduce power consumption, spatial processing complexity, and hardware costs, antenna subset selection is also performed by the proposed algorithm to choose a set of active transmit/receive antennas. The results show that combining bit allocation with spatial diversity (employing antenna subset selection) can yield substantial throughput increases.     

Detection of man‐in‐the‐middle attacks using physical layer wireless security techniques

Compared with a wired network, a wireless network is not protected by the cable transmission medium. Information is broadcasted over the air and it can be intercepted by anyone within the transmission range. Even though the transmissions could potentially be protected by security authentication mechanisms, malicious users can still intercept the information by mimicking the characteristics of normal user or a legitimate access point. This scenario is referred as a man‐in‐the‐middle (MITM) attack. In the MITM attack, the attackers can bypass the security mechanisms, intercept the unprotected transmission packets, and sniff the information. Because of several vulnerabilities in the IEEE 802.11 protocol, it is difficult to defend against a wireless MITM attack. In this paper, a received signal strength indicator (RSSI)‐based detection mechanism for MITM attacks is proposed. RSSI information is an arbitrary integer that indicates the power level being received by the antenna. The random RSSI values are processed via a sliding window, yielding statistic information about the signal characteristics such as mean and standard deviation profiles. By analyzing those profiles, the detection mechanism can detect if a rogue access point, the key component of an MITM attack, is launched. Our proposed approach has been validated via hardware experimentation using Backtrack 5 tools and MATLAB software suite. Copyright © 2014 John Wiley & Sons, Ltd.