Multipath interference causes the antenna array of an anchor to estimate several angles of arrival (AoA) for a single user. The resulting ambiguity regarding the line of sight (LoS) component can lead to severe errors in location estimation. This work formulates the problem within an outlier rejection framework: a set of candidate locations are computed by considering all AoAs at all anchors; with the observation that LoS AoA vary less than non-LoS AoA, over several time instances an inlier set can be found that clusters around the true user location. This work then derives an Ising model representation for finding the inlier set and solves the NP-hard problem using the Digital Annealer (DA). Simulations show that this approach improves median localization accuracy by 48.5% when compared to the state-of-the-art in localization methods.

This paper aims at the problem of time-of-flight (ToF) estimation using channel state information (CSI) obtainable from commercialized multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) wireless local area network (WLAN) receivers. It was often claimed that the CSI phase is contaminated with errors of known and unknown natures rendering the ToF-based positioning difficulty. To search for an answer, we take a bottom-up approach by first understanding CSI, its constituent building blocks, and the sources of error that contaminate it. We then model these effects mathematically. The correctness of these models is corroborated based on the CSI collected in extensive measurement campaign, including radiated, conducted, and chamber tests. Knowing the nature of contaminations in the CSI phase and amplitude, we proceed with introducing pre-processing methods to clean CSI from those errors and make it usable for range estimation. To check the validity of the proposed algorithms, the MUSIC super-resolution algorithm is applied to post-processed CSI to perform range estimates. The results substantiate that a median accuracy of 0.7, 0.8, and 0.9 m is achievable in a highly multipath line-of-sight environment where the transmitter and the receiver are 5, 10, and 15 m apart.

The next generation of cellular networks promises to be the platform for ubiquitous, precise, and accurate location-awareness. Although positioning using radio-frequency waves has many advantages in terms of cost and performance, propagation phenomena such as multipath propagation and shadowing can immensely deteriorate this performance leading to incorrect estimation of a user's location. This paper introduces LocHunt, an algorithm that addresses such a problem. Concretely, at each time-instance, angle-of-arrivals (AoAs) of multipath waves from several anchors are estimated and all the candidate locations of the user are derived. Repeating this operation for a span of time, the algorithm exploits the heuristics that those candidate locations obtained from non-line-of-sight (NLoS) paths exhibit large spatial variations, whereas the true location of the user is manifested as a denser cluster. Subsequently, the peak of the underlying empirical probability density function corresponds to an estimate of the user's location, which can be found by the mean-shift algorithm followed by the connected-components algorithm. The proposed data-driven approach is compared to the state-of-the-art, showing improved localization accuracy with up to one order of magnitude reduction in computational complexity. Channel state information (CSI), similar to that exposed by 802.11n MIMO-OFDM systems, is used for testing the algorithms and is generated by a modified Winner 2 (WIM2) channel simulator.

Providing from the robustness of differential chaos shift keying (DCSK) against linear and non-linear channel distortions, in this paper, we propose using this non-coherent modulation with blanking device as a potential candidate for implementation in power-line communications. The performance of this system is analyzed in the general case where background, impulsive and phase noises exist. We derive the probability of blanking error as well as the bit error rate with and without blanking. Moreover, the proposed system is compared to differential phase shift keying (DPSK) modulation to highlight the robustness of DCSK scheme against phase noise imperfection.

It is now indisputable that the performance of cognitive radio networks is closely subject to the accuracy and reliability of the inherent spectrum sensing process. In this regard, the development of an efficient sensing mechanism is an imperative task, the performance of which not only relies on the choice of the sensing function, but it substantially depends on the efficiency of the sensing data fusion, i.e. the combining of outputs from individual sensing functions. Due to its importance as well as the lack of efficient algorithms, the spectrum sensing data fusion was left as open issue in the cognitive radio IEEE 802.22 standard for wireless regional area networks (WRANs). In this research, we address this open issue by proposing a novel distributed sensing algorithm for WRANs, named single-channel learning-based distributed sensing (SC-LDS). This algorithm is self-trained, stable, and compensates for fault reports using a reward-penalty approach. Moreover, it exhibits more uniform performance in all traffic regimes, is fair (reduces the false-alarm/mis-detection gap), adjustable to different application needs, and bandwidth efficient. Simulation results unanimously corroborate that the proposed SC-LDS algorithm outperforms other techniques such as the AND, OR and VOTING rules.

The concept of a multi-interface multi-channel cognitive radio is both novel and promising. Indeed, such opportunistic access to the spectrum, over multiple channels in a simultaneous manner, will provide much higher data rates and better seamless communication while decreasing the possibility of interference to licensed users. In this vein, this paper proposes a detailed modeling and analysis of multi-interface multi-channel cognitive radio networks. The analytical efforts lead to the representation of each cognitive node with a 2-D Markov chain. Among the findings of the proposed modeling and analysis is the probability mass function of the secondary user (SU)'s queue length, from which any higher moment can be extracted. In addition, the stability condition, beyond which the network cannot be considered operative any longer, is derived. Statistical tests are conducted to determine the characteristics of the queue length's tail distribution. The accuracy of the analytical results is corroborated with simulation experiments. The proposed modeling is fairly practical as it takes into account issues such as sensing faults and channel imperfections, asynchronism among SUs, distance, and the primary activity level. In addition, the model is useful for the performance analysis and design of other types of cognitive networks as well, including cognitive-radio-based wireless regional area networks.

In this contribution, we establish a model for multi-channel cognitive radio networks (CRNs) using the theory of priority queues. This model enables us to conduct a performance analysis in the most general form by the derivation of the probability mass function (PMF) of queue length at the secondary users (SUs). In the second part, a reverse problem is considered to answer the important top-down question of whether a service requirement can be satisfied in a multi-channel CRN knowing the network parameters and traffic situation with respect to the SUs and the primary users (PUs). Terming this problem as the network synthesis, a precise conservation law is obtained, which relates the packet waiting times of both types of users, and based on which the achievable region of the network is also determined. Lastly, by the introduction of a mixed strategy, the conditions for the existence of an optimal trade-off between the interference onto the PUs and the quality-of-service of the SUs is shown, and the optimal mixed strategy is obtained when those conditions are satisfied.

The recent emergence of the cognitive radio standard IEEE 802.22 is finally empowering network operators with a new platform for their abundant services. Likewise previous wireless standards, where the modeling helped in a better understanding of the concepts and played an important role in extending the outreach of the technology and subsequent innovations, the modeling of IEEE 802.22 wireless regional area networks (WRANs) is a necessity. In this work, we accomplish this task using the theory of queues. To that end, we model the dynamics of each cognitive user, termed customer premises equipments (CPE) according to the standard terminology, with a 2-D Markov chain. Given this model, we show that a WRAN cell can be modeled as a Jackson network. We also find the probability mass function (PMF) and cumulative distribution function (CDF) of the CPE queue length, from which any higher moment can be derived. Notable is the fact that said PMF is expressed in an exact closed-form. In addition to the nodal analysis, a WRAN cell-level discussion is conducted by finding the stability condition and peer-to-peer delay. Moreover, we provide preliminary results on the resource allocation in WRANs, which is a very important area of focus and discovery for an efficient deployment and operation of future WRANs.

Small-world phenomenon is an important property of many complex networks possessing small average shortest path lengths and high clustering coefficients. On the other side, wireless ad-hoc networks are highly clustered having large average shortest path length caused by the locality of their physical connections. Since the average shortest path length (number of hops) traversed by data packets has a tight interplay with the level of quality of service experienced in the network, efforts have recently focused on the creation of small-world property in wireless networks. In this study, the concept of small world is investigated in the context of wireless ad-hoc networks in a Rayleigh fading environment. In particular, we prove that the extension of few wireless links to farther located nodes (using the concept of rewiring) can reduce the average shortest path length to a decent extent, even in the presence of severe channel fading. Simulation results show that a reduction of up to 23.3% in clustering coefficient and up to 25.6% in average shortest path length can be achieved for a low-density network in the presence of fading.

In this paper, we present an analytical study for the performance of a two-tier primary-secondary network based on IEEE 802.11 DCF mechanism. It is assumed that multiple primary users (PUs) and secondary users (SUs) coexist in the radio environment and share a single band such that the SUs are allowed to contend only if they sense the channel idle for a certain period of time. First, we derive the PUs' medium access delay in the presence of SUs. Then, assuming an exponential packet inter-arrival time for the primary network, and using M/G/1 queue modeling, we determine the collision probability and throughput for the primary and secondary networks, as well as the PUs' average total delay including the queuing delay. Numerical along with simulation results show how the performance in the primary network, with given packet arrival rate, can be affected as functions of the sensing time, packet payload size and population size of the SUs. The findings of this work can be used effectively to study the performance of any IEEE 802.11 based primary-secondary network, such as cognitive radio networks where SUs may exploit a primary channel opportunistically based on a predefined policy, as well as to optimize the performance of distributed cognitive radio MAC protocols.

In this paper, we present a cooperative transmission approach to reduce the end-to-end delay in the context of AODV based multi hop wireless networks. The underneath idea is to effectively increase the average reach of each hop so that data packets can arrive at the destination in less number of hops with lower end-to-end delay. The existing approaches of increasing transmitted power are not effective while they increase the network interferences. Unlike them, we exploit the concept of cooperative beamforming to reduce the end-to-end delay by increasing the effective communication distances and reducing the communication interferences in wireless ad-hoc networks.