Asynchronous device detection for cognitive device-to-device communications

Dynamic spectrum sharing will facilitate the interference coordination in device-to-device (D2D) communications. In the absence of network level coordination, the timing synchronization among D2D users will be unavailable, leading to inaccurate channel state estimation and device detection, especially in time-varying fading environments. In this study, we design an asynchronous device detection/discovery framework for cognitive-D2D applications, which acquires timing drifts and dynamical fading channels when directly detecting the existence of a proximity D2D device (e.g. or primary user). To model and analyze this, a new dynamical system model is established, where the unknown timing deviation follows a random process, while the fading channel is governed by a discrete state Markov chain. To cope with the mixed estimation and detection (MED) problem, a novel sequential estimation scheme is proposed, using the conceptions of statistic Bayesian inference and random finite set. By tracking the unknown states (i.e. varying time deviations and fading gains) and suppressing the link uncertainty, the proposed scheme can effectively enhance the detection performance. The general framework, as a complimentary to a network-aided case with the coordinated signaling, provides the foundation for development of flexible D2D communications along with proximity-based spectrum sharing

Cross-layer design for multimedia applications in cognitive radio networks.

Ph. D. University of KwaZulu-Natal, Durban 2015.The exponential growth in wireless services and the current trend of development in wireless communication technologies have resulted into an overcrowded radio spectrum band in such a way that it can no longer meet the ever increasing requirements of wireless applications. In contrary however, literature surveys indicate that a large amount of the licensed radio spectrum bands are underutilized. This has necessitated the need for efficient ways to be implemented for spectrum sharing among different systems, applications and services in dynamic wireless environment. Cognitive radio (CR) technology emerges as a way to improve the overall efficiency of radio spectrum utilization by allowing unlicensed users (also known as secondary user) to utilize a licensed band when it is vacant. Multimedia applications are being targeted for CR networks. However, the performance and success of CR technology will be determined by the quality of service (QoS) perceived by secondary users. In order to transmit multimedia contents which have stringent QoS requirements over the CR networks, many technical challenges have to be addressed that are constrained by the layered protocol architecture. Cross-layer design has shown a promise as an approach to optimize network performance among different layers. This work is aimed at addressing the question on how to provide QoS guarantee for multimedia transmission over CR networks in terms of throughput maximization while ensuring that the interference to primary users is avoided or minimized. Spectrum sensing is a fundamental problem in cognitive radio networks for the protection of primary users and therefore the first part of this work provides a review of some low complex spectrum sensing schemes. A cooperative spectrum sensing scheme where multi-users are independently performing spectrum sensing is also developed. In order to address a hidden node problem, a cooperate relay based on amplify-and-forward technique (AF) is formulated. Usually the performance of a spectrum sensor is evaluated using receiver operating characteristic (ROC) curve which provides a trade-off between the probability of miss detection and the probability of false alarm. Due to hardware limitations, the spectrum sensor can not sense the whole range of radio spec- trum which results into partial information of the channel state. In order to model a media access control(MAC) protocol which is able to make channel access decision under partial information about the state of the system we apply a partially observable Markov decision process (POMDP) technique as a suitable tool in making decision under uncertainty. A throughput optimization MAC scheme in presence of spectrum sensing errors is then devel- oped using the concept of cross-layer design which integrates the design of spectrum sensing at physical layer (PHY) and sensing and access strategies at MAC layer in order to maximize the overall network throughput. A problem is formulated as a POMDP and the throughput performance of the scheme is evaluated using computer simulations under greedy sensing algorithm. Simulation results demonstrate an improved overall throughput performance. Further more, multiple channels with multiple secondary users having random message ar- rivals are considered during simulation and the throughput performance is evaluated under greedy sensing scheme which forms a benchmark for cross-layer MAC scheme in presence of spectrum sensing errors. By realizing that speech communication is still the most dom- inant and common service in wireless application, we develop a cross-layer MAC scheme for speech transmission in CR networks. The design is aimed at maximizing throughput of secondary users by integrating the design of spectrum sensing at PHY, quantization param- eter of speech traffic at application layer (APP), together with strategy for spectrum access at MAC layer with the main goal to improve the QoS perceived by secondary users in CR networks. Simulation results demonstrate throughput performance improvement and hence QoS is improved. One of the main features of the modern communication systems is the parameterized operation at different layers of the protocol stack. The feature aims at providing them with the capability of adapting to the rapidly changing traffic, channel and system conditions. Another interesting research problem in this thesis is the combination of individual adap- tation mechanisms into a cross-layer that can maximize their effectiveness. We propose a joint cross-layer design MAC scheme that integrates the design of spectrum sensing at PHY layer, access at MAC layer and APP information in order to improve the QoS for video transmission in CR networks. The end-to-end video distortion which is considered as an APP parameter resides in the video encoder. This is integrated in the state space and the problem is formulated as a constrained POMDP. H.264 coding algorithm which is one of the high efficient video coding standards is considered. The objective is to minimize this end-to- end video distortion while maximizes the overall network throughput for video transmission in CR networks. The end-to-end video distortion has signifficant effects to the QoS the per- ceived by the user and is viewed as the cost in the overall system design. Given the target system throughput, the packet loss ration when the system is in the state i and a composite action is taken in time slot t, the system immediate cost is evaluated. The expected total cost for overall end-to-end video distortion over the total time slots is then computed. A joint optimal policy which minimizes the expected total end-to-end distortion in total time slots is computed iteratively. The minimum expected cost (which also known as the value function) is also evaluated iteratively for the total time slots. The throughput performance of the proposed scheme is evaluated through computer simulation. In order to study the throughput performance of the proposed scheme, we considered four simulation scenarios namely simulation scenario A, simulation scenario B, simulation scenario C, and simulation scenario D. These simulation scenarios enabled us to study the throughput performance of the proposed scheme by by computer simulations. In the simulation scenario A, the av- erage throughput performance as a function of time horizon is studied. The throughput performance under channel access decision based on belief vector and that of channel access decision based on the end-to-end distortion are compared. Simulation results show that the channel access decision based on end-to-end distortion outperforms that of channel access decision based on a belief vector. In the simulation scenario B we aimed at studying the spectral efficiency as a function of prescribed collision probability. The simulation results show that, at large values of collision probability the overall spectral efficiency performs poorly. However, there is an optimal value of collision probability of which the spectral efficiency approaches that of the perfect channel access decision. In the simulation scenario C, we aimed at studying the average throughput performance and the spectral efficiency both as a function of prescribed collision probability. The simulation results show that both average throughput and the spectral efficiency are highly affected by the increase in collision probability. However, there is an optimal prescribed collision probability which achieves the maximum average throughput and maximum spectral efficiency

Dual-battery empowered green cellular networks

With awareness of the potential harmful effects to the environment and climate change, on-grid brown energy consumption of information and communications technology (ICT) has drawn much attention. Cellular base stations (BSs) are among the major energy guzzlers in ICT, and their contributions to the global carbon emissions increase sustainedly. It is essential to leverage green energy to power BSs to reduce their on-grid brown energy consumption. However, in order to furthest save on-grid brown energy and decrease the on-grid brown energy electricity expenses, most existing green energy related works only pursue to maximize the green energy utilization while compromising the services received by the mobile users. In reality, dissatisfaction of services may eventually lead to loss of market shares and profits of the network providers. In this research, a dual-battery enabled profit driven user association scheme is introduced to jointly consider the traffic delivery latency and green energy utilization to maximize the profits for the network providers in heterogeneous cellular networks. Since this profit driven user association optimization problem is NP-hard, some heuristics are presented to solve the problem with low computational complexity. Finally, the performance of the proposed algorithm is validated through extensive simulations. In addition, the Internet of Things (IoT) heralds a vision of future Internet where all physical things/devices are connected via a network to promote a heightened level of awareness about our world and dramatically improve our daily lives. Nonetheless, most wireless technologies utilizing unlicensed bands cannot provision ubiquitous and quality IoT services. In contrast, cellular networks support large-scale, quality of service guaranteed, and secured communications. However, tremendous proximal communications via local BSs will lead to severe traffic congestion and huge energy consumption in conventional cellular networks. Device-to-device (D2D) communications can potentially offload traffic from and reduce energy consumption of BSs. In order to realize the vision of a truly global IoT, a novel architecture, i.e., overlay-based green relay assisted D2D communications with dual batteries in heterogeneous cellular networks, is introduced. By optimally allocating the network resource, the introduced resource allocation method provisions the IoT services and minimizes the overall energy consumption of the pico relay BSs. By balancing the residual green energy among the pico relay BSs, the green energy utilization is maximized; this furthest saves the on-grid energy. Finally, the performance of the proposed architecture is validated through extensive simulations. Furthermore, the mobile devices serve the important roles in cellular networks and IoT. With the ongoing worldwide development of IoT, an unprecedented number of edge devices imperatively consume a substantial amount of energy. The overall IoT mobile edge devices have been predicted to be the leading energy guzzler in ICT by 2020. Therefore, a three-step green IoT architecture is proposed, i.e., ambient energy harvesting, green energy wireless transfer and green energy balancing, in this research. The latter step reinforces the former one to ensure the availability of green energy. The basic design principles for these three steps are laid out and discussed. In summary, based on the dual-battery architecture, this dissertation research proposes solutions for the three aspects, i.e., green cellular BSs, green D2D communications and green devices, to hopefully and eventually actualize green cellular access networks, as part of the ongoing efforts in greening our society and environment

Optimization and learning algorithms for orthogonal frequency division multiplexing-based dynamic spectrum access.

Ph.DDOCTOR OF PHILOSOPH

Joint spectrum sensing and access for stable dynamic spectrum aggregation

International audienc

A Tutorial on Joint Radar and Communication Transmission for Vehicular Networks-Part II: State of the Art and Challenges Ahead

In Part I of this three-part tutorial on dual-functional radar-communication (DFRC), we overviewed the fundamental elements of DFRC. As Part II of the tutorial, this letter overviews the state-of-the-art (SoA) in DFRC, with a particular emphasis on the use of the technique for seamless connectivity in the vehicular network. We commence by introducing the conventional beam tracking approaches for millimeter wave (mmWave) communication systems, based exclusively on communication signalling and feedback, followed by the DFRC based schemes tailored for the vehicular network. Finally, we evaluate a number of SoA DFRC schemes through comparative simulations

Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems

A Real Time Radio Spectrum Scanning Technique Based On The Bayesian Model And Its Comparison With The Frequentist Technique

The proliferation of mobile devices led to an exponential demand for wireless radio spectrum resources. The current fixed spectrum assignment has caused some portions of the radio spectrum to be heavily used whereas others to be scarcely used. This has resulted in underutilization of spectrum resources, and, hence has demanded the need for solutions to address the spectrum scarcity problem. Cognitive radio was proposed as one of the solutions. One of the techniques involved in cognitive radio is the dynamic spectrum access technique. This technique requires the identification of free channels in order to allow secondary users to exploit the spectrum resources. The process of identification of free channels is known as radio spectrum scanning, which is performed by sensing a particular channel in the radio spectrum to determine the presence or absence of a signal. In most of existing studies, the frequentist technique using energy detection with fixed threshold was used to scan the radio spectrum. However, this method comes with a major drawbacks. First, energy detection is unable to distinguish between signals and noise and suffer for high false detection rates. Second, energy detection has high false alarm probability. Finally, frequentist techniques are subject to uncertainty and do not provide real time monitoring/sensing. Therefore, the goal of this thesis is to develop a more efficient scanning technique that deals with uncertainty and scans the radio spectrum in real time and determines its occupancy levels. An enhanced spectrum scanning approach is developed using an efficient spectrum sensing technique: an uncertainty handling Bayesian model along with a Bayesian inferential approach. Two Bayesian models are developed: 1) a simplified model, and 2) an improved model to incorporate the Bayesian inferential approach to estimate the spectrum occupancy level. The performance evaluation of the proposed technique has been done using simulations as well as real experiments. For this purpose, two metrics were used: probability of detection and probability of false alarm. Furthermore, the efficiency of the proposed technique was compared to the efficiency of the frequentist technique, which uses only a spectrum sensing technique to identify the occupancy of the spectrum channels. As expected significant improvements in the spectrum occupancy measurements have been observed with the proposed Bayesian inference method