168 research outputs found

    Capacity -based parameter optimization of bandwidth constrained CPM

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    Continuous phase modulation (CPM) is an attractive modulation choice for bandwidth limited systems due to its small side lobes, fast spectral decay and the ability to be noncoherently detected. Furthermore, the constant envelope property of CPM permits highly power efficient amplification. The design of bit-interleaved coded continuous phase modulation is characterized by the code rate, modulation order, modulation index, and pulse shape. This dissertation outlines a methodology for determining the optimal values of these parameters under bandwidth and receiver complexity constraints. The cost function used to drive the optimization is the information-theoretic minimum ratio of energy-per-bit to noise-spectral density found by evaluating the constrained channel capacity. The capacity can be reliably estimated using Monte Carlo integration. A search for optimal parameters is conducted over a range of coded CPM parameters, bandwidth efficiencies, and channels. Results are presented for a system employing a trellis-based coherent detector. To constrain complexity and allow any modulation index to be considered, a soft output differential phase detector has also been developed.;Building upon the capacity results, extrinsic information transfer (EXIT) charts are used to analyze a system that iterates between demodulation and decoding. Convergence thresholds are determined for the iterative system for different outer convolutional codes, alphabet sizes, modulation indices and constellation mappings. These are used to identify the code and modulation parameters with the best energy efficiency at different spectral efficiencies for the AWGN channel. Finally, bit error rate curves are presented to corroborate the capacity and EXIT chart designs

    Modulation classification of digital communication signals

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    Modulation classification of digital communications signals plays an important role in both military and civilian sectors. It has the potential of replacing several receivers with one universal receiver. An automatic modulation classifier can be defined as a system that automatically identifies the modulation type of the received signal given that the signal exists and its parameters lie in a known range. This thesis addresses the need for a universal modulation classifier capable of classifying a comprehensive list of digital modulation schemes. Two classification approaches are presented: a decision-theoretic (DT) approach and a neural network (NN) approach. First classifiers are introduced that can classify ASK, PSK, and FSK signals. A decision tree is designed for the DT approach and a NN structure is formulated und trained to classify these signals. Both classifiers use the same key features derived from the intercepted signal. These features are based on the instantaneous amplitude, instantaneous phase, and instantaneous frequency of the intercepted signal, and the cumulates of its complex envelope. Threshold values for the DT approach are found from the minimum total error probabilities of the extracted key features at SNR of 20 to -5dB. The NN parameters are found by training the networks on the same data. The DT and NN classifiers are expanded to include CPM signals. Signals within the CPM class are also added to the classifiers and a separate decision tree and new NN structure are found far these signals. New key features to classify these signals are also introduced. The classifiers are then expanded further to include multiple access signals, followed by QAM, PSK8 and FSK8 signals. New features arc found to classify these signals. The final decision tree is able to accommodate a total of fifteen different modulation types. The NN structure is designed in a hierarchical fashion to optimise the classification performance of these fifteen digital modulation schemes. Both DT and NN classifiers are able to classify signals with more than 90% accuracy in the presence of additive white Gaussian within SNR ranging from 20 to 5dB. However, the performance of the NN classifier appears to be more robust as it degrades gradually at the SNRs of 0 and -5dB. At -5dB, the NN has an overall accuracy of 73.58%, whereas the DT classifier achieves only 47.3% accuracy. The overall accuracy of the NN classifier, over the combined SNR range of 20 to -5dB, is 90.7% compared to 84.56% for the DT classifier. Finally, the performances of these classifiers are tested in the presence of Rayleigh fading. The DT and NN classifier structures are modified to accommodate fading and again, new key features are introduced to accomplish this. With the modifications, the overall accuracy of the NN classifier, over the combined SNR range of 20 to -5dB and 120Hz Doppler shift, is 87.34% compared to 80.52% for the DT classifier

    Joint Detection and Decoding of High-Order Modulation Schemes for CDMA and OFDM Wireless Communications

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    Wireless communications call for high data rate, power and bandwidth efficient transmissions. High-order modulation schemes are suitable candidates for this purpose as the potential to reduce the symbol period is often limited by the multipath-induced intersymbol interference. In order to reduce the power consumption, and at the same time, to estimate time-variant wireless channels, we propose low-complexity, joint detection and decoding schemes for high-order modulation signals in this dissertation. We start with the iterative demodulation and decoding of high-order CPM signals for mobile communications. A low complexity, pilot symbol-assisted coherent modulation scheme is proposed that can significantly improve the bit error rate performance by efficiently exploiting the inherent memory structure of the CPM modulation. A noncoherent scheme based on multiple symbol differential detection is also proposed and the performances of the two schemes are simulated and compared. Second, two iterative demodulation and decoding schemes are proposed for quadrature amplitude modulated signals in flat fading channels. Both of them make use of the iterative channel estimation based on the data signal reconstructed from decoder output. The difference is that one of them has a threshold controller that only allows the data reconstructed with high reliability values to be used for iterative channel estimation, while the other one directly uses all reconstructed data. As the second scheme has much lower complexity with a performance similar to the best of the first one, we further apply it to the space-time coded CDMA Rake receiver in frequency-selective multipath channels. We will compare it to the pilot-aided demodulation scheme that uses a dedicated pilot signal for channel estimation. In the third part of the dissertation, we design anti-jamming multicarrier communication systems. Two types of jamming signals are considered - the partial-band tone jamming and the partial-time pulse jamming. We propose various iterative schemes to detect, estimate, and cancel the jamming signal in both AWGN and fading channels. Simulation results demonstrate that the proposed systems can provide reliable communications over a wide range of jamming-to-signal power ratios. Last, we study the problem of maximizing the throughput of a cellular multicarrier communication network with transmit or receive diversity. The total throughput of the network is maximized subject to power constraints on each mobile. We first extend the distributed water-pouring power control algorithm from single transmit and receive antenna to multiple transmit and receive antennas. Both equal power diversity and selective diversity are considered. We also propose a centralized power control algorithm based on the active set strategy and the gradient projection method. The performances of the two algorithms are assessed with simulation and compared with the equal power allocation algorithm

    A General Framework for Analyzing, Characterizing, and Implementing Spectrally Modulated, Spectrally Encoded Signals

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    Fourth generation (4G) communications will support many capabilities while providing universal, high speed access. One potential enabler for these capabilities is software defined radio (SDR). When controlled by cognitive radio (CR) principles, the required waveform diversity is achieved via a synergistic union called CR-based SDR. Research is rapidly progressing in SDR hardware and software venues, but current CR-based SDR research lacks the theoretical foundation and analytic framework to permit efficient implementation. This limitation is addressed here by introducing a general framework for analyzing, characterizing, and implementing spectrally modulated, spectrally encoded (SMSE) signals within CR-based SDR architectures. Given orthogonal frequency division multiplexing (OFDM) is a 4G candidate signal, OFDM-based signals are collectively classified as SMSE since modulation and encoding are spectrally applied. The proposed framework provides analytic commonality and unification of SMSE signals. Applicability is first shown for candidate 4G signals, and resultant analytic expressions agree with published results. Implementability is then demonstrated in multiple coexistence scenarios via modeling and simulation to reinforce practical utility

    Performance improvements in wireless CDMA communications utilizing adaptive antenna arrays

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    This dissertation studies applications of adaptive antenna arrays and space-time adaptive processing (STAP) in wireless code-division multiple-access (CDMA) communications. The work addresses three aspects of the CDMA communications problems: (I) near-far resistance, (2) reverse link, (3) forward link. In each case, adaptive arrays are applied and their performance is investigated. The near-far effect is a well known problem which affects the reverse link of CDMA communication systems. The near-far resistance of STAP is analyzed for two processing methods: maximal ratio combining and optimum combining. It. is shown that while maximal ratio combining is not near-far resistant, optimum combining is near-far resistant when the number of cochannel interferences is less than the system dimensionality. The near-far effect can be mitigated by accurate power control at the mobile station. With practical limitations, the received signal power at a base station from a power-controlled user is a random variable clue to power control error. The statistical model of signal-to-interference ratio at the antenna array output of a base station is presented, and the outage probability of the CDMA reverse link is analyzed while considering Rayleigh fading, voice activity and power control error. New analytical expressions are obtained and demonstrated by computer simulations. For the application of an adaptive antenna. array at the forward link, a receiver architecture is suggested for the mobile station that utilizes a small two-antenna array For interference suppression. Such a receiver works well only when the channel vector of the desired signal is known. The identifying spreading codes (as in IS-95A for example) are used to provide an adaptive channel vector estimate, and control the beam steering weight, hence improve the receiver performance. Numerical results are presented to illustrate the operation of the proposed receiver model and the improvement in performance and capacity

    連続位相変調方式の広帯域無線システムへの適用に関する研究

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    信州大学(Shinshu university)博士(工学)Thesis森岡 和行. 連続位相変調方式の広帯域無線システムへの適用に関する研究. 信州大学, 2014, 博士論文. 博士(工学), 甲第614号, 平成26年9月30日授与.doctoral thesi
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