Cognitive radio (CR) is a novel wireless communication approach that may alleviate the looming spectrum-shortage crisis. Orthogonal frequency division multiplexing (OFDM) is an attractive modulation candidate for CR systems. In this thesis, we study resource allocation (RA) for OFDM-based CR systems using both aggressive and protective sharing. In aggressive sharing, cognitive radio users (CRUs) can share both non-active and active primary user (PU) bands. We develop a model that describes aggressive sharing, and formulate a corresponding multidimensional knapsack problem (MDKP). Low-complexity suboptimal RA algorithms are proposed for both single and multiple CRU systems. A simplified model is proposed which provides a faster suboptimal solution. Simulation results show that the proposed suboptimal solutions are close to optimal, and that aggressive sharing of the whole band can provide a substantial performance improvement over protective sharing, which makes use of only the non-active PU bands. Although aggressive sharing generally yields a higher spectrum-utilization efficiency than protective sharing, aggressive sharing may not be feasible in some situations. In such cases, sharing only non-active PU bands is more appropriate. When there are no fairness or quality of service (QoS) considerations among CRUs, both theoretical analysis and simulation results show that plain equal power allocation (PEPA) yields similar performance as optimal power allocation in a multiuser OFDM-based CR system. We propose a low-complexity discrete bit PEPA algorithm. To improve spectrum-utilization efficiency, while considering the time-varying nature of the available spectrum as well as the fading characteristics of wireless communication channels and providing QoS provisioning and fairness among users, this thesis introduces the following novel algorithms: (1) a distributed RA algorithm that provides both fairness and efficient spectrum usage for ad hoc systems; (2) a RA algorithm for non-real-time (NRT) services that maintains average user rates proportionally on the downlink of multiuser OFDM-based CR systems; and (3) cross-layer RA algorithms for the downlink of multiuser OFDM-based CR systems for both real-time (RT) services and mixed (RT and NRT) services. Simulation results show that the proposed algorithms provide satisfactory QoS to all supported services and perform better than existing algorithms designed for multiuser OFDM systems.

Cooperative communication is a promising technique for wireless communication systems where wireless nodes cooperate together in transmitting their information. Such communication transmission technique, which realizes the multiple antenna arrays in a distributed manner over multiple wireless nodes, succeeds in extending the network coverage, increasing throughput, improving both link reliability and spectral efficiency. Available channel state information at the transmitting nodes can be used to design adaptive transmission schemes for improving the overall system performance. Throughout our work, we adaptively change loaded power and/or bit to the Orthogonal Frequency Division Multiplexing (OFDM) symbol in order to minimize bit error rate or maximize the throughput. In the first part of this dissertation, we consider single-relay OFDM system with amplify-and-forward relaying. We propose three algorithms to minimize the bit error rate under total power constraint and fixed transmission rate. These algorithms are optimal power loading, optimal bit loading and optimal bit and power loading. Through Monte Carlo simulations we study the proposed system performance and discuss the effect of relay location and channel estimation. This study shows that the proposed algorithms result in exploiting the multi-path diversity and achieving extra coding gain. In the second part, we extend the problem to a multi-relay OFDM network but with decode-and-forward relaying. We propose an adaptive power loading algorithm to minimize the bit error rate under total power constraint based on two relay selection strategies. The proposed system leads to achieve both multi-path and cooperative spatial diversity using maximal-ratio combiner for the detection. In the last part, we consider also multi-relay network but with amplify and forward relaying. We optimize the bit loading coefficients to maximize the throughput under target bit error rate constraint. The proposed algorithm is considered more practical since it takes into consideration the channel estimation quality. The considered adaptive system has less complexity compared with other adaptive systems through reducing the feedback amount. Furthermore, the full network channel state information is needed only at the destination.

Cognitive radio is an autonomous transceiver that is continuously sensing theongoing communication in its environment, it then starts the communication whenever it is appropriate. Therefore, cognitive radio helps improving the spectrum utilization of the overall communication system. However, without suitable spectrum sensing techniques, cognitive radio would fail. Hence, in this thesis we investigate and implement various spectrum sensing algorithms via software defined radio for both single antenna and multiple antenna cases. The main communi-cation scheme that we are using is OFDM. Moreover, both computer simulations and real-world measurements, have also been done for comparison and analysis ofthe detector’s performance. The detectors we are using are based on correlationfunction of the received signal and generalized likelihood ratio test with its eigen-value. The results from the simulations and measurements are then representedas probability of missed detection curves for different signal to noise ratios. Ourresults show that the performance of the generalized likelihood ratio test baseddetectors are at least 2 dB better than the correlation based detector in our mea-surement. Moreover, our simulations show that they are able to outperform thecorrelation function detector by more than 6 dB. Although, generalized likelihoodratio test based detectors seem to be better than the correlation function baseddetector, it requires more computational power which may limit its practical use.

les travaux portent sur la mise en oeuvre d'un système de communication sur une plate-forme SUNDANCE, comportnat DSP et fPGA.<br />Les techniques MIMO, OFDM et CDMA sont combinées afin de profiter de la diversité fréquentielle, spatiale<br />Un nouveau schéma de codage MIMO / OFDM est proposé

With the increasing demand for more wireless multimedia applications, it is desired to design a wireless system with higher data rate. Furthermore, the frequency spectrum has become a limited and valuable resource, making it necessary to utilize the available spectrum efficiently and coexist with other wireless systems. Orthogonal frequency division multiplexing (OFDM) modulation is widely used in communication systems to meet the demand for ever increasing data rates. The major advantage of OFDM over single-carrier transmission is its ability to deal with severe channel conditions without complex equalization. However, OFDM systems suffer from a high peak to average power ratio, and they are sensitive to carrier frequency offset and Doppler spread. This dissertation first focuses on the development of intercarrier interference (ICI) reduction and signal detection algorithms for OFDM systems over time-varying channels. Several ICI reduction algorithms are proposed for OFDM systems over doubly-selective channels. The OFDM ICI reduction problem over time-varying channels is formulated as a combinatorial optimization problem based on the maximum likelihood (ML) criterion. First, two relaxation methods are utilized to convert the ICI reduction problem into convex quadratic programming (QP) problems. Next, a low complexity ICI reduction algorithm applicable to $M$-QAM signal constellations for OFDM systems is proposed. This formulates the ICI reduction problem as a QP problem with non-convex constraints. A successive method is then utilized to deduce a sequence of reduced-size QP problems. For the proposed algorithms, the QP problems are solved by limiting the search in the 2-dimensional subspace spanned by its steepest-descent and Newton directions to reduce the computational complexity. Furthermore, a low-bit descent search (LBDS) is employed to improve the system performance. Performance results are given to demonstrate that the proposed ICI reduction algorithms provide excellent performance with reasonable computational complexity. A low complexity joint semiblind detection algorithm based on the channel correlation and noise variance is proposed which does not require channel state information. The detection problem is relaxed to a continuous non-convex quadratic programming problem. Then an iterative method is utilized to deduce a sequence of reduced-size quadratic programming problems. A LBDS method is also employed to improve the solution of the derived QP problems. Results are given which demonstrate that the proposed algorithm provides similar performance with lower computational complexity compared to that of a sphere decoder. A major challenge to OFDM systems is how to obtain accurate channel state information for coherent detection of the transmitted signals. Thus several channel estimation algorithms are proposed for OFDM systems over time-invariant channels. A channel estimation method is developed to utilize the noncircularity of the input signals to obtain an estimate of the channel coefficients. It takes advantage of the nonzero cyclostationary statistics of the transmitted signals, which in turn allows blind polynomial channel estimation using second-order statistics of the OFDM symbol. A set of polynomial equations are formulated based on the correlation of the received signal which can be used to obtain an estimate of the time domain channel coefficients. Performance results are presented which show that the proposed algorithm provides better performance than the least minimum mean-square error (LMMSE) algorithm at high signal to noise ratios (SNRs), with low computational complexity. Near-optimal performance can be achieved with large OFDM systems. Finally, a CS-based time-domain channel estimation method is presented for OFDM systems over sparse channels. The channel estimation problem under consideration is formulated as a small-scale $l_1$-minimization problem which is convex and admits fast and reliable solvers for the globally optimal solution. It is demonstrated that the magnitudes as well as delays of the significant taps of a sparse channel model can be estimated with satisfactory accuracy by using fewer pilot tones than the channel length. Moreover, it is shown that a fast Fourier transform (FFT) matrix of extended size can be used as a set of appropriate basis vectors to enhance the channel sparsity. This technique allows the proposed method to be applicable to less-sparse OFDM channels. In addition, a total-variation (TV) minimization based method is introduced to provide an alternative way to solve the original sparse channel estimation problem. The performance of the proposed method is compared to several established channel estimation algorithms. / Graduate

As diverse and data-heavy underwater applications emerge, demanding requirements are further imposed on underwater wireless communication systems. Future underwater wireless communication networks might consist of both mobile and stationary nodes which exchange data such as control, telemetry, speech, and video signals among themselves as well as a central node located at a ship or onshore. The submerged nodes, which can, for example, take the form of an autonomous underwater vehicle/robot or diver, can be equipped with various sensors, sonars, video cameras, or other types of data acquisition instruments. Innovative physical layer solutions are therefore required to develop efficient, reliable, and high-speed transmission solutions tailored for challenging and diverse requirements of underwater applications. Building on the promising combination of multi-carrier and cooperative communication techniques, this dissertation investigates the fundamental performance bounds of cooperative underwater acoustic (UWA) communication systems taking into account the inherent unique characteristics of the UWA channel. We derive outage probability and capacity expressions for cooperative multi-carrier UWA systems with amplify-and-forward and decode-and-forward relaying. Through the derived expressions, we demonstrate the effect of several system and channel parameters on the performance. Furthermore, we investigate the performance of cooperative UWA systems in the presence of non-uniform Doppler distortion and propose receiver designs to mitigate the degrading Doppler effects.

No description available.

Orthogonal frequency division multiplexing (OFDM) has become a popular modulation method in high-speed wireless communications. By partitioning a wideband fading channel into flat narrowband channels, OFDM is able to mitigate the detrimental effects of multipath fading using a simple one-tap equalizer. However, in the time domain OFDM signals suffer from large envelope variations, which are often characterized by the peak-to-average ratio (PAR). High PAR signals, like OFDM, require that transmission amplifiers operate at very low power efficiencies to avoid clipping. In this dissertation, we explore the problems associated with transmitted OFDM signals through peak limited channels. A large part of this work deals with analyzing different distortion metrics and determining which metrics are most useful. We find that the signal-to-noise-plus-distortion ratio (SNDR) is one of the most important metrics in assessing distortion in nonlinear channels. As part of this analysis, we compare sample-based SNDR and symbol-based SNDR and find that using the more comprehensive symbol-based metric as the objective in SNDR maximization algorithms leads to only marginal SNDR improvements. The SNDR perspective is also applied to existing PAR-reduction techniques to compare existing schemes and proposed new schemes. Part of this work involves deriving a SNDR maximizing adaptation of the popular PAR-reduction scheme, selected mapping (SLM). We also compare another popular PAR-reduction method, partial transmit sequence (PTS), to SLM through a variety of metrics including SNDR and found that for any given amount of complexity or side information SLM provided better performance. The next major piece of work in this dissertation addresses synchronization and channel estimation in peak-limited channels for OFDM. We build off of existing work that shows that embedded synchronization energy is a more bandwidth efficient means of synchronization than preamble-base methods. With this, we demonstrate a method for generating embedded sequences that have low PAR, and thus minimize the PAR of the combination OFDM symbol/embedded sequence among all embedded sequences. Next, we extend this work to sequences called joint synchronization-pilot sequences (JSPSs) by deriving the symbol-estimate mean squared error (MSE) pilot placements for the JSPSs and by showing how the JSPSs can be used with SLM for blind detection. Finally, the dissertation concludes with a derivation of the SNDR-optimal transmitter/receiver pairs. Using functional analysis, we show that the SNDR-optimal receivers for peak-limited transmitters are not linear. Instead they follow non-linear functions that depend on the noise and signal distributions.

The efficient use of radio resources is crucial in order for future wireless systems to be able to meet the demand for high speed data communication services. Orthogonal Frequency Division Multiplexing (OFDM) is an important technology for future wireless systems as it offers numerous advantages over other existing technologies, such as robust performance over multipath fading channels and the ability to achieve high spectral efficiency. Dynamic resource allocation can fully exploit the advantages of OFDM, especially in multiple user systems. In this thesis, we investigate a resource allocation problem in a multiple user, multiple cell OFDM cellular network focusing on downlink communications. (For complete abstract open document)

Zugl.: Dresden, Techn. Univ., Diss., 2007