Resource Allocation in OFDM-Based Cognitive Two-Way Relay Networks

Cognitive radio (CR), nowadays, is considered as one of the most promising techniques which introduce the flexible usage of radio spectrum and improve the spectral efficiency by enabling unlicensed users to exploit the licensed spectrum in an opportunistic manner. Moreover, the two-way relay communication has attracted a great attention as it introduces a relaying scheme with a bidirectional transmission to exchange information between two nodes. This strategy assumed to improve the overall capacity, since less time slots are needed than the one-way strategy, besides extending the radio coverage range of networks. Another common technique that improves the bandwidth efficiency and spectrum utilization is the orthogonal frequency division multiplexing (OFDM) technique which exhibits a distinctive efficiency in mitigating inter-symbol interference (ISI) and combating frequency selective fading. Therefore, two-way relay CR communication among OFDM terminals can take advantage of these three techniques to boost up the capacity together with the networks quality. In this thesis, an OFDM-based amplify and forward (AF), cognitive two-way multiple-relay network is considered where two transceiver nodes exchange information via relay nodes. The full transmission happens in two time slots. In the first time slot, multiple access phase (MA), the transceiver nodes send their signals to the relay nodes while in the second time slot, broadcast phase (BC), the relay nodes broadcast the received signals to the transceivers. In this dissertation, the problem to jointly optimize the network resources is considered. The first is the transmission power of transceivers and relay nodes to ensure suitable allocated power for best signals transmission besides ensuring no harmful interference is caused to the primary system. The other important resource to be optimized is the subcarrier pairing where the first and second time slots subcarriers have to be matched such that the subcarriers with the best conditions is reserved. The final tuned resource, in this work, is the relay selection where the relay node that assures the best transition of the received signal is selected. The dual decomposition technique is applied to get the optimal resource allocation. Moreover, suboptimal algorithms are proposed to perform the resource allocation reducing, significantly, the computational complexity compared with the optimal solution with small performance degradation. Finally, simulation results of the suggested AF OFDM cognitive relaying network are shown to compare the performance gain of the different algorithms which reveals that the proposed suboptimal algorithm achieves good performance with much less computational complexity than the optimal one

Air Force Institute of Technology Research Report 2005

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, and Engineering Physics

Spectrally-Temporally Adapted Spectrally Modulated Spectrally Encoded (SMSE) Waveform Design for Coexistent CR-Based SDR Applications

This work expands the applicability of the Spectrally Modulated, Spectrally Encoded (SMSE) framework by developing a waveform optimization process that enables intelligent waveform design. The resultant waveforms are capable of adapting to a spectrally diverse transmission channel while meeting coexistent constraints. SMSE waveform design is investigated with respect to two different forms of coexisting signal constraints, including those based on resultant interference levels and those based on resultant power spectrum shape. As demonstrated, the SMSE framework is well-suited for waveform optimization given its ability to allow independent design of spectral parameters. This utility is greatly enhanced when soft decision selection and dynamic assignment of SMSE design parameters are incorporated. Results show that by exploiting statistical knowledge of primary user spectral and temporal behavior, the inherent flexibility of the SMSE framework is effectively leveraged such that SMSE throughput (Bits/Sec) is maximized while limiting mutual coexistent interference to manageable levels

On The Dynamic Spectrum Access For Next Generation Wireless Communication Systems

Ph.DDOCTOR OF PHILOSOPH

High capacity high spectral efficiency transmission techniques in wireless broadband systems

Ph.DDOCTOR OF PHILOSOPH