In this thesis study, a new method for automatic recognition of intrapulse modulations has been proposed. This new method deals the problem of modulation recognition with a feature-based approach. The features used to recognize the modulation type are Instantaneous Frequency, Instantaneous Bandwidth, Amplitude Modulation Depth, Box Dimension and Information Dimension. Instantaneous Bandwidth and Instantaneous Frequency features are extracted via Autoregressive Spectrum Modeling. Amplitude Modulation Depth is used to express the depth of amplitude change on the signal. The other features, Box Dimension and Information Dimension, are extracted using Fractal Theory in order to classify the modulations on signals depending on their shapes. A modulation database is used in association with Fractal Theory to decide on the modulation type of the analyzed signal, by means of a distance metric among fractal dimensions. Utilizing these features in a hierarchical flow, the new modulation recognition method is achieved. The proposed method has been tested for various intrapulse modulation types. It has been observed that the method has acceptably good performance even for low SNR cases and for signals with small PW.

High Frequency (3-30 MHz) (HF) Ionospheric Channel is used for military, civilian and amateur communications. By using Ionosphere, communication for distances beyond the line of sight is achieved. The main advantage of this type of communication is that it does not to require a satellite to communicate with a point beyond the line of sight. Actually the Ionosphere is used instead of a satellite. To use Ionosphere but not a satellite means independent communication for a country. The disadvantage of HF Ionospheric Communication is that the characteristics of the reflecting media (i.e. channel&rsquo / s transfer function) depends on many variables, e.g. sun spot number, hour of the day, season, solar cycles etc., so that mathematically modeling the channel is very difficult. Since military standards like STANAG 4538, STANAG 4285, STANAG 4415, MIL-STD-188-110A and MIL-STD-188-141A define the required performance of an HF modem in terms of Signal to Noise Ratio (SNR), Doppler Spread and Delay Spread according to desired conditions, a new approach to characterize the channel in terms of these three parameters is presented. In this thesis, HF Channel is considered as a system which involves various physical and chemical processes. A new method to characterize the HF channel to be used for modem performance evaluation is presented. In this study, it is aimed to relate modem/channel availability with the magnetic indices, which may be considered as the disturbances to the system. For this purpose the data taken from an HF communication experiment is used to model the channel to be used for modem availability calculations. The aim of the study is to asses the HF Channel Availability under Ionospheric Disturbances. This new technique will be a useful tool for HF Modem operators to select the optimum data rate or modulation method during HF Communication.

The primary challenge in wireless sensor network (WSN) deployment is the limited network lifetime due to the finite-capacity batteries. In accordance with this challenge, the vast majority of research efforts thus far have focused on the development of energy-efficient communication and computing mechanisms for WSNs. In this thesis, a fundamentally different approach and hence completely new WSN paradigm, i.e., the Passive Wireless Sensor Network (PWSN), is introduced. The objective of PWSN is to eliminate the limitation on the system lifetime of the WSNs. In PWSN, power is externally supplied to the sensor network node via an external RF source. Hence, the lifetime of the system is no longer determined by the lifetime of the batteries. An alternative communication scheme, modulated backscattering, is also discussed to be utilized in PWSN. The feasibility of the proposed system is investigated along with the open research challenges for reliable communication and networking in PWSN. Additionally, a new medium access schemee for PWSN, Ultra-Wideband PWSN Medium Access Control (UWB PWSN MAC), is presented.

Low-density parity-check (LDPC) codes are a subclass of linear block codes. These codes have parity-check matrices in which the ratio of the non-zero elements to all elements is low. This property is exploited in defining low complexity decoding algorithms. Low-density parity-check codes have good distance properties and error correction capability near Shannon limits. In this thesis, the sum-product and the bit-flip decoding algorithms for low-density parity-check codes are implemented on Intel Pentium M 1,86 GHz processor using the software called MATLAB. Simulations for the two decoding algorithms are made over additive white gaussian noise (AWGN) channel changing the code parameters like the information rate, the blocklength of the code and the column weight of the parity-check matrix. Performance comparison of the two decoding algorithms are made according to these simulation results. As expected, the sum-product algorithm, which is based on soft-decision decoding, outperforms the bit-flip algorithm, which depends on hard-decision decoding. Our simulations show that the performance of LDPC codes improves with increasing blocklength and number of iterations for both decoding algorithms. Since the sum-product algorithm has lower error-floor characteristics, increasing the number of iterations is more effective for the sum-product decoder compared to the bit-flip decoder. By having better BER performance for lower information rates, the bit-flip algorithm performs according to the expectations / however, the performance of the sum-product decoder deteriorates for information rates below 0.5 instead of improving. By irregular construction of LDPC codes, a performance improvement is observed especially for low SNR values.

In this study we tried to design a microstrip antenna, to get a suitable radiation pattern for a LEO satellite. Our aim is to get a radiation pattern that has a maximum power which is not in the broadside direction to the antenna surface / instead broadside radiation has a relatively lower power density. Maximum power radiation is desired to be at about 30 &ndash / 50 degrees angle beyond the normal to the antenna surface. We desire circularly polarized radiation. We used two concentric antennas / one is a circular patch at the center and the other is an annular ring which is used at the outer region. By using Ansoft Ensemble 8.0 software, we design an antenna which has a resonance frequency at 8.2 GHz. Using the result of the program we design the real antenna. The measurement results are compared with the simulation results.

In this thesis, DOA estimation using array interpolation in randomly distributed sensor arrays is considered. Array interpolation is a technique in which a virtual array is obtained from the real array and the outputs of the virtual array, computed from the real array using a linear transformation, is used for direction of arrival estimation. The idea of array interpolation techniques is to make simplified and computationally less demanding high resolution direction finding methods applicable to the general class of non-structured arrays.In this study,we apply an interpolation technique for arbitrary array geometries in an attempt to extend root-MUSIC algorithm to arbitrary array geometries.Another issue of array interpolation related to direction finding is spatial smoothing in the presence of multipath sources.It is shown that due to the Vandermonde structure of virtual array manifold vector obtained from the proposed interpolation method, it is possible to use spatial smoothing algorithms for the case of multipath sources.

In this thesis, we present low latency general concatenated code structures suitable for parallel processing. We propose parallel decodable serially concatenated codes (PDSCCs) which is a general structure to construct many variants of serially concatenated codes. Using this most general structure we derive parallel decodable serially concatenated convolutional codes (PDSCCCs). Convolutional product codes which are instances of PDSCCCs are studied in detail. PDSCCCs have much less decoding latency and show almost the same performance compared to classical serially concatenated convolutional codes. Using the same idea, we propose parallel decodable turbo codes (PDTCs) which represent a general structure to construct parallel concatenated codes. PDTCs have much less latency compared to classical turbo codes and they both achieve similar performance. We extend the approach proposed for the construction of parallel decodable concatenated codes to trellis coded modulation, turbo channel equalization, and space time trellis codes and show that low latency systems can be constructed using the same idea. Parallel decoding operation introduces new problems in implementation. One such problem is memory collision which occurs when multiple decoder units attempt accessing the same memory device. We propose novel interleaver structures which prevent the memory collision problem while achieving performance close to other interleavers.

In this thesis, symbol timing recovery based on matched filtering in Gaussian Minimum Shift Keying (GMSK) with bandwidth-bit period product (BT) of 0.3 is investigated. GMSK is the standard modulation type for GSM. Although GMSK modulation is non-linear, it is approximated to Offset Quadrature Amplitude Modulation (OQAM), which is a linear modulation, so that Maximum Likelihood Sequence Estimation (MLSE) method is possible in the receiver part. In this study Typical Urban (TU) channel model developed in COST 207 is used. Two methods are developed on the construction of the matched filter. In order to obtain timing recovery for GMSK signals, these methods are investigated. The fractional time delays are acquired by using interpolation and an iterative maximum search process. The performance of the proposed symbol timing recovery (STR) scheme is assessed by using computer simulations. It is observed that the STR tracks the variations of the frequency selective multipath fading channels almost the same as the Mazo criterion.

In Wireless Sensor Actor Networks (WSANs), sensor nodes perform the sensing task and actor nodes take action based on the sensed phenomenon. The presence of actors in this configuration can not be benefited from, unless they are able to execute actions at right place and right time in the event region. The right place can be related to the accurate position of the sensor nodes. While, the right time is related to delivering the packets directly to the appropriate actors within the event specific response times. Hence, the efficient localization of sensor nodes, sensor-actor/actor-actor coordination and real-time routing is indispensable in WSANs. Furthermore, the limited energy levels and bandwidth of the state of art sensor nodes currently impose stringent requirements for low-complexity, low-energy, distributed coordination and cooperation protocols and their implementation. In this study, we propose an integrated framework which addresses the issues of sensors localization, network configuration, data aggregation, real-time data delivery, sensor-actor/actor-actor coordination and energy saving mechanisms. The proposal incorporates novel approaches on three fronts / (1) timing-based sensors localization (TSL) algorithm to localize the sensor nodes relative to actors, (2) real-time coordination and routing protocols and (3) energy conservation. The distributed real-time coordination and routing is implemented in addressing and greedy modes routing. A cluster-based real-time coordination and routing (RCR) protocol operates in addressing mode. The greedy mode routing approach (Routing by Adaptive Targeting, RAT) is a stateless shortest path routing. In dense deployment, it performs well in terms of delay and energy consumption as compared to RCR. To keep the traffic volume under control, the framework incorporates a novel real-time data aggregation (RDA) approach in RCR such that the packets deadlines are not affected. RDA is adaptive to the traffic conditions and provides fairness among the farther and nearer cluster-heads. Finally, framework incorporates a power management scheme that eliminates data redundancy by exploiting the spatial correlation of sensor nodes. Simulation results prove that the framework provides the real-time guarantees up to 95 % of the packets with lesser energy consumption of up to 33 % achieved using MEAC as compared to LEACH and SEP. The packet delivery ratio is also 60 % higher than that of semi-automated architecture. Furthermore the action accuracy is supported by TSL which restricts the localization errors less than 1 meter by tuning it according to the expected velocity of nodes and required accuracy.

Inverse Synthetic Aperture Radar coherently processes the return signal from the target in order to construct the image of the target. The conventional methodology used for obtaining the image is the Fourier transform which is not capable of suppressing the Doppler change in the return signal. As a result, Range-Doppler image is degraded. A proper time-frequency transform suppresses the degradation due to time varying Doppler shift. In this thesis, high resolution joint-time frequency transformations that can be used in place of the conventional method are evaluated. Wigner-Ville Distribution, Adaptive Gabor Representation with Coarse-to-Fine search algorithm, and Time-Frequency Distribution Series are examined for the target imaging system. The techniques applied to sample signals compared with each other. The computational and memorial complexity of the methods are evaluated and compared to each other and possible improvements are discussed. The application of these techniques in the target imaging system is also performed and resulting images compared to each other.