Improved Energy Detector for Wideband Spectrum Sensing in Cognitive Radio Networks

In this paper, an improved energy detector for a wideband spectrum sensing is proposed. For a better detection of the spectrum holes the overall band is divided into equal non-overlapping sub-bands. The main objective is to determine the detection thresholds for each of these subbands jointly. By defining the problem as an optimization problem, we aim to find the maximum aggregated opportunistic throughput of cognitive radio networks. Introducing practical constraints to this optimization problem will change the problem into a convex and solvable one. The results of this paper show that the proposed improved energy detector will increase the aggregated throughput considerably

Building accurate radio environment maps from multi-fidelity spectrum sensing data

In cognitive wireless networks, active monitoring of the wireless environment is often performed through advanced spectrum sensing and network sniffing. This leads to a set of spatially distributed measurements which are collected from different sensing devices. Nowadays, several interpolation methods (e.g., Kriging) are available and can be used to combine these measurements into a single globally accurate radio environment map that covers a certain geographical area. However, the calibration of multi-fidelity measurements from heterogeneous sensing devices, and the integration into a map is a challenging problem. In this paper, the auto-regressive co-Kriging model is proposed as a novel solution. The algorithm is applied to model measurements which are collected in a heterogeneous wireless testbed environment, and the effectiveness of the new methodology is validated

Topology Control, Scheduling, and Spectrum Sensing in 5G Networks

The proliferation of intelligent wireless devices is remarkable. To address phenomenal traffic growth, a key objective of next-generation wireless networks such as 5G is to provide significantly larger bandwidth. To this end, the millimeter wave (mmWave) band (20 GHz -300 GHz) has been identified as a promising candidate for 5G and WiFi networks to support user data rates of multi-gigabits per second. However, path loss at mmWave is significantly higher than today\u27s cellular bands. Fortunately, this higher path loss can be compensated through the antenna beamforming technique-a transmitter focuses a signal towards a specific direction to achieve high signal gain at the receiver. In the beamforming mmWave network, two fundamental challenges are network topology control and user association and scheduling. This dissertation proposes solutions to address these two challenges. We also study a spectrum sensing scheme which is important for spectrum sharing in next-generation wireless networks. Due to beamforming, the network topology control in mmWave networks, i.e., how to determine the number of beams for each base station and the beam coverage, is a great challenge. We present a novel framework to solve this problem, termed Beamforming Oriented tOpology coNtrol (BOON). The objective is to reduce total downlink transmit power of base stations in order to provide coverage of all users with a minimum quality of service. BOON smartly groups nearby user equipment into clusters to dramatically reduce interference between beams and base stations so that we can significantly reduce transmit power from the base station. We have found that on average BOON uses only 10%, 32%, and 25% transmit power of three state-of-the-art schemes in the literature. Another fundamental problem in the mmWave network is the user association and traffic scheduling, i.e., associating users to base stations, and scheduling transmission of user traffic over time slots. This is because base station has a limited power budget and users have very diverse traffic, and also require some minimum quality of service. User association is challenging because it generally does not rely on the user distance to surrounding base stations but depends on if a user is covered by a beam. We develop a novel framework for user association and scheduling in multi-base station mmWave networks, termed the clustering Based dOwnlink user assOciation Scheduling, beamforming with power allocaTion (BOOST). The objective is to reduce the downlink network transmission time of all users\u27 traffic. On average, BOOST reduces the transmission time by 37%, 30%, and 26% compared with the three state-of-the-art user scheduling schemes in the literature. At last, we present a wavelet transform based spectrum sensing scheme that can simultaneously sense multiple subbands, even without knowing how the subbands are divided, i.e., their boundaries. It can adaptively detect all active subband signals and, thus, discover the residual spectrum that can be used by unlicensed devices

On demonstrating spectrum selection functionality for opportunistic networks

This paper presents a testbed platform to demonstrate and validate spectrum opportunity identification and spectrum selection functionalities in Opportunistic Networks (ONs). The hardware component of the testbed is based on reconfigurable devices able to transmit and receive data at different operating frequencies, which are dynamically configured. The software component has been developed to perform the creation and maintenance of ON radio links, including spectrum opportunity identification and selection decision making as well as all the necessary signaling to support the ON operation. Therefore, the presented platform provides a powerful tool for testing different algorithms in real operational radio environments under various interference conditions, thus enabling to gain deeper insight into the performance of algorithmic solutions, beyond the purely theoretical analyses based on models and/or simulations. Results presented in the paper validate the implementation conducted at the laboratory and illustrate the reconfigurability capabilities of the ON links under different conditions.Peer ReviewedPostprint (published version

Spectrum Sensing and Sharing for Cognitive Radar Systems

The IEEE 802.22 standard specifies the air interface, including the cognitive medium access control layer (MAC) and physical layer (PHY), of point-to-multipoint wireless regional area networks (WRAN) comprised of a professional fixed Base Station (BS) with fixed and portable user terminals, referred as the Customer Premise Equipment (CPE) devices, operating in the white spaces in the VHF/UHF TV broadcast bands while avoiding interference to the incumbent broadcast services. This work focuses on a Passive Coherent Location (PCL) system that exploits the signals emitted by IEEE 802.22 devices and is referred hereafter as a White Space PCL (WS-PCL) system. To cope with the very low transmitted EIRP of the IEEE 802.22 emitters, we focus on the design of a WS-PCL system that exploits all the useful signals received in each frame, and therefore the signals emitted from both the BS and CPEs. In this work we study the feasibility of the WS-PCL system, we derive the Receiver Operating Characteristic (ROC) of the WS-PCL receiver and we define a multistatic velocity profiling algorithm for the estimation of the target velocity vector. The performances of the proposed receiver are compared with those of a WS-PCL system that exploits only the signal emitted by the BS