Transmission Cooperative Strategies for MIMO-OFDM Heterogeneous Networks

Mobile traffic in cellular networks is increasing exponentially, mainly due to the use of data intensive services like video. One way to cope with these demands is to reduce the cell-size by deploying small-cells along the coverage area of the current macro-cell system. The deployment of small-cells significantly improves indoor coverage. Nevertheless, as additional spectrum licenses are difficult and expensive to acquire it is expected that the macro and small-cells will coexist under the same spectrum. The coexistence of the two systems results in crosstier/ inter-system interference. In this context, we design several interference alignment based techniques for the downlink of heterogeneous networks, in order to cancel the interference generated from macro-cell at small-cell user terminals. More specifically, in this contribution we design interference alignment methods under different levels of inter-system coordination and the constraint that the performance of macro-cell system is kept close to the case where small-cell system is switched-off. Numerical results demonstrate that the proposed methods achieve close to the optimal performance with low overhea

Homogeneous Test-bed for Cognitive Radio

In the current frequency allocation scheme, the radio spectrum is found to be heavily underutilized in time, frequency and space dimensions or any of their combination. To improve spectrum utilization, the unused contiguous or non-contiguous portion of the radio spectrum (spectrum hole) can be accessed opportunistically using cognitive radio technology provided it is interference free to the local users of the network. To reliably detect the spectrum holes, which is necessary to limit the interference, cognitive radio is required to have high time and frequency resolutions to detect radio technologies (e.g. GSM 900, 2.4 GHz WLAN) at the packet level in the transmitted channel to avoid misinterpretation of occupancy states in time and frequency. In addition, having high sensitivity and instantaneous dynamic range can enable cognitive radio to detect weak received signals and their detection in the presence of strong received signals. Besides these requirements, a large sensing bandwidth can increase the chances to find spectrum holes in multiple radio technologies concurrently. A chirp channel sounder receiver has been developed according to the aforementioned requirements with a bandwidth of 750 MHz to provide reliable detection of received signals in two frequency ranges; 1) 250 MHz to 1 GHz, 2) 2.2 GHz to 2.95 GHz. The developed receiver is capable of finding spectrum holes having a duration of 204.8 μs and a transmitted channel bandwidth up to 200 kHz. To explore the spectrum holes in the space dimensions, six chirp channel sounder receivers have been developed to form a homogeneous test-bed, which can be deployed and controlled independently. To experimentally validate the ability of the built receiver, short term spectrum occupancy measurements have been conducted to monitor 2.4 GHz WLAN traffic from a real wireless network to quantify the spectrum utilization and duration of spectrum holes in the time domain. It has been found that the radio spectrum is underutilized and empirical distribution of the duration of the spectrum hole can be modelled using lognormal and gamma distributions for prediction using a two state continuous time semi-Markov model. To experimentally validate the receiver’s capabilities in both the supported frequency ranges, long term spectrum occupancy measurements with 750 MHz sensing bandwidth have been performed and received signals have been detected at frame or packet level to quantify spectrum utilization. It has been found that the radio spectrum is highly underutilized at the measurement location and exhibits significant amount of spectrum holes in both time and frequency. To experimentally validate the functionalities of the homogeneous test-bed, short term spectrum occupancy have been performed to monitor 2.4 GHz WLAN traffic from a real wireless network. The experiment has been conducted using multiple receivers to quantify the amount of cooperation individual or multiple cognitive radio users can provide for reliable detection of spectrum holes in time, frequency and space. It has been found that the space dimension influences strongly the statistics of cooperation parameters

TOWARD ENHANCED WIRELESS COEXISTENCE IN THE 2.4GHZ ISM BAND VIA TEMPORAL CHARACTERIZATION AND EMPIRICAL MODELING OF 802.11B/G/N NETWORKS A DISSERTATION

This dissertation presents an extensive experimental characterization and empirical modelling of 802.11 temporal behavior. A detailed characterization of 802.11b/g/n homogeneous and heterogeneous network traffic patterns is featured, including idle time distribution and channel utilization. Duty cycle serves as a measure for spectrum busyness. Higher duty cycle levels directly impact transceivers using the spectrum, which either refrain from transmission or suffer from increased errors. Duty cycle results are provided for 802.11b, g and n Wi-Fi technologies at various throughput levels. Lower values are observed for 802.11b and g networks. Spectrum occupancy measurements are essential for wireless networks planning and deployment. Detailed characterization of 802.11g/n homogeneous and heterogeneous network traffic patterns, including activity and idle time distribution are presented. Distributions were obtained from time domain measurements and represent time fragment distributions for active and inactive periods during a specific test. This information can assist other wireless technologies in using the crowded ISM band more efficiently and achieve enhanced wireless coexistence. Empirical models of 802.11 networks in the 2.4 GHz Industrial, Scientific, and Medical (ISM) band are also presented. This information can assist other wireless technologies aiming to utilize the crowded ISM band more efficiently and achieve enhanced wireless coexistence. In this work models are derived for both homogeneous and heterogeneous 802.11 network idle time distribution. Additionally, two applications of 802.11 networks temporal characterization are presented. The first application investigates a novel method for identifying wireless technologies through the use of simple energy detection techniques to measure the channel temporal characteristics including activity and idle time probability distributions. In this work, a wireless technology identification algorithm was assessed experimentally. Temporal traffic pattern for 802.11b/g/n homogeneous and heterogeneous networks were measured and used as algorithm input. Identification accuracies of up to 96.83% and 85.9% are achieved for homogeneous and heterogeneous networks, respectively. The second application provides a case study using 802.15.4 ZigBee transmitter packet size on-line adjustments is also presented. Packet size is adaptively modified based on channel idle time distribution obtained using simple channel power measurements. Results demonstrate improved ZigBee performance and significant enhancement in throughput as a result of using adaptive packet size transmissions

Intelligent Approaches for Energy-Efficient Resource Allocation in the Cognitive Radio Network

The cognitive radio (CR) is evolved as the promising technology to alleviate the spectrum scarcity issues by allowing the secondary users (SUs) to use the licensed band in an opportunistic manner. Various challenges need to be addressed before the successful deployment of CR technology. This thesis work presents intelligent resource allocation techniques for improving energy efficiency (EE) of low battery powered CR nodes where resources refer to certain important parameters that directly or indirectly affect EE. As far as the primary user (PU) is concerned, the SUs are allowed to transmit on the licensed band until their transmission power would not cause any interference to the primary network. Also, the SUs must use the licensed band efficiently during the PU’s absence. Therefore, the two key factors such as protection to the primary network and throughput above the threshold are important from the PU’s and SUs’ perspective, respectively. In deployment of CR, malicious users may be more active to prevent the CR users from accessing the spectrum or cause unnecessary interference to the both primary and secondary transmission. Considering these aspects, this thesis focuses on developing novel approaches for energy-efficient resource allocation under the constraints of interference to the PR, minimum achievable data rate and maximum transmission power by optimizing the resource parameters such as sensing time and the secondary transmission power with suitably selecting SUs. Two different domains considered in this thesis are the soft decision fusion (SDF)-based cooperative spectrum sensing CR network (CRN) models without and with the primary user emulation attack (PUEA). An efficient iterative algorithm called iterative Dinkelbach method (IDM) is proposed to maximize EE with suitable SUs in the absence of the attacker. In the proposed approaches, different constraints are evaluated considering the negative impact of the PUE attacker on the secondary transmission while maximizing EE with the PUE attacker. The optimization problem associated with the non-convex constraints is solved by our proposed iterative resource allocation algorithms (novel iterative resource allocation (NIRA) and novel adaptive resource allocation (NARA)) with suitable selection of SUs for jointly optimizing the sensing time and power allocation. In the CR enhanced vehicular ad hoc network (CR-VANET), the time varying channel responses with the vehicular movement are considered without and with the attacker. In the absence of the PUE attacker, an interference-aware power allocation scheme based on normalized least mean square (NLMS) algorithm is proposed to maximize EE considering the dynamic constraints. In the presence of the attacker, the optimization problem associated with the non-convex and time-varying constraints is solved by an efficient approach based on genetic algorithm (GA). Further, an investigation is attempted to apply the CR technology in industrial, scientific and medical (ISM) band through spectrum occupancy prediction, sub-band selection and optimal power allocation to the CR users using the real time indoor measurement data. Efficacies of the proposed approaches are verified through extensive simulation studies in the MATLAB environment and by comparing with the existing literature. Further, the impacts of different network parameters on the system performance are analyzed in detail. The proposed approaches will be highly helpful in designing energy-efficient CRN model with low complexity for future CR deployment