Relay techniques have the potential to enhance capacity and coverage of a wireless network. Due to rapidly increasing number of smart phone subscribers and high demand for data intensive multimedia applications, the useful radio spectrum is becoming a scarce resource. For this reason, two way relay network and cognitive radio technologies are required for better utilization of radio spectrum. Compared to the conventional one way relay network, both the uplink and the downlink can be served simultaneously using a two way relay network. Hence the effective bandwidth efficiency is considered to be one time slot per transmission. Cognitive networks are wireless networks that consist of different types of users, a primary user (PU, the primary license holder of a spectrum band) and secondary users (SU, cognitive radios that opportunistically access the PU spectrum). The secondary users can access the spectrum of the licensed user provided they do not harmfully affect to the primary user. In this thesis, various resource allocation and optimization techniques have been investigated for wireless relay and cognitive radio networks.

In this dissertation, I focus on source coding techniques as well as channel coding techniques. I addressed the challenges in WSN by developing (1) a new source coding strategy for erasure channels that has better distortion performance compared to MDC; (2) a new cooperative channel coding strategy for multiple access channels that has better channel outage performances compared to MIMO; (3) a new source-channel cooperation strategy to accomplish source-to-fusion center communication that reduces system distortion and improves outage performance. First, I draw a parallel between the 2x2 MDC scheme and the Alamouti's space time block coding (STBC) scheme and observe the commonality in their mathematical models. This commonality allows us to observe the duality between the two diversity techniques. Making use of this duality, I develop an MDC scheme with pairwise complex correlating transform. Theoretically, I show that MDC scheme results in: 1) complete elimination of the estimation error when only one descriptor is received; 2) greater efficiency in recovering the stronger descriptor (with larger variance) from the weaker descriptor; and 3) improved performance in terms of minimized distortion as the quantization error gets reduced. Experiments are also performed on real images to demonstrate these benefits. Second, I present a two-phase cooperative communication strategy and an optimal power allocation strategy to transmit sensor observations to a fusion center in a large-scale sensor network. Outage probability is used to evaluate the performance of the proposed system. Simulation results demonstrate that: 1) when signal-to-noise ratio is low, the performance of the proposed system is better than that of the MIMO system over uncorrelated slow fading Rayleigh channels; 2) given the transmission rate and the total transmission SNR, there exists an optimal power allocation that minimizes the outage probability; 3) on correlated slow fading Rayleigh channels, channel correlation will degrade the system performance in linear proportion to the correlation level. Third, I combine the statistical ranking of sensor observations with cooperative communication strategy in a cluster-based wireless sensor network. This strategy involves two steps: 1) ranking the sensor observations based on their test statistics; 2) building a two-phase cooperative communication model with an optimal power allocation strategy. The result is an optimal system performance that considers both sources and channels. I optimize the proposed model through analyses of the system distortion, and show that the cooperating nodes achieve maximum channel capacity. I also simulate the system distortion and outage to show the benefits of the proposed strategies.

New underwater passive sonar techniques are developed for enhancing target localization capabilities in shallow ocean environments. The ocean surface and the seabed act as acoustic mirrors that reflect sound created by boats or subsurface vehicles, which gives rise to echoes that can be heard by hydrophone receivers (underwater microphones). The goal of this work is to leverage this "multipath" phenomenon in new ways to determine the origin of the sound, and thus the location of the target. However, this is difficult for propeller driven vehicles because the noise they produce is both random and continuous in time, which complicates its measurement and analysis. Further, autonomous underwater vehicles (AUVs) pose additional challenges because very little is known about the sound they generate, and its similarity to that of boats. Existing methods for localizing propeller noise using multiple hydrophones have approached the problem either purely theoretically, or empirically such as by analyzing the interference patterns between multipath arrivals at different frequencies, however little has been published on building localization techniques that directly measure and utilize the time delays between multipath arrivals while simultaneously accounting for relevant environmental parameters. This research develops such techniques through a combination of array beamforming and advanced ray-based modeling that account for variations in bathymetry (seabed topography) as well as variations of the sound speed of the water. The basis for these advances come from several at-sea experiments in which different configurations of passive sonar systems recorded sounds emitted by different types of targets, including small boats and an autonomous underwater vehicle. Ultimately, these contributions may reduce the complexity and cost of passive systems that need to be deployed close to shore, such as for harbor security applications. Further, they also create new possibilities for applying passive sonar in remote ocean regions for tasks such as detecting illegal fishing activity. This dissertation makes three key contributions: 1. Analysis of the aspect-dependent acoustic radiation patterns of an underway autonomous underwater vehicle (AUV) through full-field wave modeling. 2. A two-hydrophone cross-correlation technique that leverages multipath as well as bathymetric variations to estimate the range and bearing of a small boat, supported by a mathematically rigorous performance analysis. 3. A multi-target localization technique based on directly measuring multipath from multiple small surface vessels using a small hydrophone array mounted to the nose of an AUV, which operates by cross-correlating two elevation beams on a single bearing.

This study evaluated a time-restricted region-suppressed event-related synthetic aperture magnetoencephalography (TRRS-ER-SAM) beamformer algorithm against equivalent current dipole (ECD), and event-related synthetic aperture magnetoencephalography (ER-SAM) post-processing methods for magnetoencephalography data. This evaluation was done numerically and with auditory evoked field (AEF) data elicited by binaurally presented 500 Hz tones. The TRRS-ER-SAM beamformer demonstrated robustness to noise, and the ability to handle coherent sources. The TRRS-ER-SAM algorithm was then applied to a study of N1m AEFs in 8 subjects aged 12-25 years. The study examined the effects of age, stimulus frequency, and right-sided monaural versus binaural stimulation on the N1m location, amplitude, and latency. It was found that age affected the N1m latency; stimulus frequency affected the N1m location, amplitude, and latency; and monaural versus binaural stimulation affected the N1m amplitude. In the context of these effects, the auditory pathway structure and neurophysiological changes due to maturation were discussed.

This study evaluated a time-restricted region-suppressed event-related synthetic aperture magnetoencephalography (TRRS-ER-SAM) beamformer algorithm against equivalent current dipole (ECD), and event-related synthetic aperture magnetoencephalography (ER-SAM) post-processing methods for magnetoencephalography data. This evaluation was done numerically and with auditory evoked field (AEF) data elicited by binaurally presented 500 Hz tones. The TRRS-ER-SAM beamformer demonstrated robustness to noise, and the ability to handle coherent sources. The TRRS-ER-SAM algorithm was then applied to a study of N1m AEFs in 8 subjects aged 12-25 years. The study examined the effects of age, stimulus frequency, and right-sided monaural versus binaural stimulation on the N1m location, amplitude, and latency. It was found that age affected the N1m latency; stimulus frequency affected the N1m location, amplitude, and latency; and monaural versus binaural stimulation affected the N1m amplitude. In the context of these effects, the auditory pathway structure and neurophysiological changes due to maturation were discussed.

No description available.

With the increasing demand of higher data rate for telecommunication, the IEEE802.11n standard was constituted in 2009. Themost important character of the standard is MIMO-OFDM, which not only improves the throughput but also the spectrumefficiency and channel capacity. This report focuses on the physical layer IEEE802.11n model. By utilizing an existingSimulink based IEEE802.11n system, functionalities like MIMO (up to 4*4), OFDM, STBC, Beamforming, and MMSEdetector are simulated. The results such as bit error rate, packet error rate and bit rate with different system settings are given.Furthermore, the channel estimation process is clarified, and a DSP builder based MMSE detector is realized, which can fulfillexactly the same function as the Simulink model.

Recent years have brought many new developments in the processing of speech and acoustic signals. Yet, despite this, the process of acquiring signals has gone largely unchanged. Adding spatial diversity to the repertoire of signal acquisition has long been known to offer advantages for processing signals further. The processing capabilities of mobile devices had not previously been able to handle the required computation to handle these previous streams of information. But current processing capabilities are such that the extra workload introduced by the addition of mutiple sensors on a mobile device are not over-burdensome. How these extra data streams can best be handled is still an open question. The present work deals with the examination of one type of spatial processing technique, known as beamforming. A microphone array test platform is constructed and verified through a number of beamforming agorithms. Issues related to speech acquisition through microphones arrays are discussed. The algorithms used for verification are presented in detail and compared to one another.

In the thesis, we investigate transmit beamforming strategies in a wireless cooperative network consisting of one source, one destination and multi relays that adopt amplify-and-forward (AF). In our scheme, small amount of information feedback from the destination, each relays perturbs individually based beamforming coefficient. Perturbation-based beamforming have been proposed in [16], where the authors assume that the channel is time-invariant, and every relay node can not acquire channel state information (CSI) after receiving pilot sequence signals, the relays multiply the pilot sequence with two perturbed beamforming vectors, and forward two weighted training sequence to destination. At the destination, the signal to noise ratio (SNR) of two received training sequence are evaluated and compared. Finally, the destination compare with SNRs. To indicate the result of compared SNRs, destination feedback one-bit message to inform relays the comparison results, and then relays update beamforming vector based on one-bit message. After several iteration, the beamforming vector will approach the optimum one. However, in time-varying environment, the updating rata of beamforming vector in the method with one-bit feedback may be more slowly than rate of channel variation. The contribution of this thesis is to propose transmit beamforming scheme with two-bit or finite-bit feedback to accommodate to the time-varying environment. In our proposed scheme, the destination linearly combines two received sequence corresponding to two different beamforming vectors with various weighting factors. After evaluating and comparing the SNRs of combined signals, the destination notifies the optimum linear combining factors using a multi-bit feedback message. Based on the feedback message, relays can update the beamforming vector correspondingly. In chapter five, it shows through computer simulations that our proposed scheme can raise average SNR and reduce bit error rate effectively.

In this thesis, the problem of quantifying the Pareto optimal boundary of the achievable rate region is considered over multiple-input single-output(MISO)interference channels, where the problem boils down to solving a sequence of convex feasibility problems after certain transformations. The feasibility problem is solved by two new distributed optimal beam forming algorithms, where the first one is to parallelize the computation based on the method of alternating projections, and the second one is to localize the computation based on the method of cyclic projections. Convergence proofs are established for both algorithms.