Signal-to-noise ratio (SNR) estimation is one of the important research topics in wireless communications. In the receiver, many algorithms require SNR information to achieve optimal performance. In this thesis, an autocorrelation based SNR estimator is proposed. The proposed method utilizes the correlation properties of symbol sequence and the uncorrelated properties of noise sequence to distinguish the signal power from the received signal. Curve fitting method is used for SNR estimator to predict the signal power. Mean and variance performance of the proposed SNR estimator is compared with that of the conventional SNR estimator by computer simulations. These simulations consider additive white Gaussian noise and multipath Rayleigh fading channel with BPSK, 8PSK, 16QAM and 64QAM modulation schemes. According to the simulation results, the proposed method can provide better performance than conventional methods in both mean and mean-square-error.

In this thesis, we introduce a signal-to-noise ratio (SNR) estimator and analyze the performance degradation of the SNR estimator due to the synchronization error in the orthogonal frequency division multiplexing (OFDM) systems. This SNR estimator through the expectation-maximization (EM) algorithm is used in the adaptive modulation. When the synchronization is imperfectly done, the synchronization error reduces the performance of the OFDM systems and the accuracy of the SNR estimator. We investigate the estimation offset of the SNR estimator with the synchronization error. Simulation results demonstrate that the theoretical analyses are correct. In addition, the simulation results show that the more synchronization errors cause the more estimation errors of the SNR estimator. And the estimation errors are not decreased by the iteration of the EM algorithm.

In many algorithms for Orthogonal Frequency Division Multiplexing (OFDM) systems, the channel estimation is one of the most essential factors. In wireless environment, channel is change very fast, and the channel has multipath effect, the channel length is obtained by channel estimation. In this paper, we estimation the channel length and the SNR by virtual carriers (VC) and Singular value decomposition, when channel estimator known the information for channel length, then calculate complicated can be reduced. Besides, we proposed the estimated method at carriers frequency offset effect. Noise variance (or noise power) can improve performance of channel estimator, e.g. MMSE channel estimator, turbo code or power allocation. In this paper, we were estimate noise variance by using the blind method of property of orthogonality of matrix, which is differed from the traditional method of Pilots.

The rapid growth in wireless communications has given rise to an increasing demand for channel capacity using limited bandwidth. Wireless channels vary over time due to fading and changing interference conditions. Typical wireless systems are designed by choosing a modulation scheme to meet worst case conditions and thus rely on power control to adapt to changing channel conditions. Adaptive modulation, however, exploits these channel variations to improve the spectral efficiency of wireless communications by intelligently changing the modulation scheme based on channel conditions. Necessarily, among the modulation schemes used are spectrally efficient modulation schemes such as quadrature amplitude modulation (QAM) techniques. QAM yields the high spectral efficiency due to its use of amplitude as well as phase modulation and therefore is an effective technique for achieving high channel capacity. The main drawbacks of QAM modulation are its reduced energy efficiency (as compared to standard QPSK) and its sensitivity to channel amplitude variations. Adaptive modulation attempts to address the first drawback by using more energy efficient schemes in low SNR conditions are reserving the use of QAM for high SNR conditions. The second drawback leads to a requirement of high quality channel estimation. Many researchers have studied pilot symbol assisted modulation for compensating the effects of fading at the receiver. A main contribution of this thesis is the investigation of different channel estimation techniques (along with the effect of pilot symbol spacing and Doppler spread) on the performance of adaptive modulation. Another important parameter affecting adaptive modulation is the signal-to-noise ratio. In order to adapt modulation efficiently, it is essential to have accurate knowledge of the channel signal-to-noise ratio. The performance of adaptive modulation depends directly on how well the channel SNR is estimated. The more accurate the estimation of the channel SNR is, the better the choice of modulation scheme becomes, and the better the ability to exploit the variations in the wireless channel is. The second main contribution of this thesis is the investigation of the impact of SNR estimation techniques on the performance and spectral efficiency of adaptive modulation. Further, we investigate the impact of various channel conditions on SNR estimation and the resulting impact on the performance of adaptive modulation. Finally, we investigate long term SNR estimation, its use in adaptive modulation and present a comparison between the two approaches / Master of Science

Multi-hop wireless transmission, where radios forward the message of other radios, is becoming popular both in cellular as well as sensor networks. This research is concerned with the statistical modeling of multi-hop wireless networks that do cooperative transmission (CT). CT is a physical layer wireless communication scheme in which spatially separated wireless nodes collaborate to form a virtual array antenna for the purpose of increased reliability. The dissertation has two major parts. The first part addresses a special form of CT known as the Opportunistic Large Array (OLA). The second part addresses the signal-to-noise ratio (SNR) estimation for the purpose of recruiting nodes for CT. In an OLA transmission, the nodes from one level transmit the message signal concurrently without any coordination with each other, thereby producing transmit diversity. The receiving layer of nodes receives the message signal and repeats the process using the decode-and-forward cooperative protocol. The key contribution of this research is to model the transmissions that hop from one layer of nodes to another under the effects of channel variations, carrier frequency offsets, and path loss. It has been shown for a one-dimensional network that the successive transmission process can be modeled as a quasi-stationary Markov chain in discrete time. By studying various properties of the Markov chain, the system parameters, for instance, the transmit power of relays and distance between them can be optimized. This optimization is used to improve the performance of the system in terms of maximum throughput, range extensions, and minimum delays while delivering the data to the destination node using the multi-hop wireless communication system. A major problem for network sustainability, especially in battery-assisted networks, is that the batteries are drained pretty quickly during the operation of the network. However, in dense sensor networks, this problem can be alleviated by using a subset of nodes which take part in CT, thereby saving the network energy. SNR is an important parameter in determining which nodes to participate in CT. The more distant nodes from the source having least SNR are most suitable to transmit the message to next level. However, practical real-time SNR estimators are required to do this job. Therefore, another key contribution of this research is the design of optimal SNR estimators for synchronized as well as non-synchronized receivers, which can work with both the symbol-by-symbol Rayleigh fading channels as well as slow flat fading channels in a wireless medium.

One of the fundamental hurdles in realizing new spectrum sharing allocation policies is that of reliable spectrum sensing. In this thesis, three research thrusts are presented in order to further research in this critical area. The first of these research thrusts is the development of a novel asynchronous and noncoherent modulation classifier for PSK/QAM modulated signals in flat-fading channels. In developing this classifier, a novel estimator for the unknown channel gain and fractional time delay is proposed which uses a method-of-moments based estimation approach. For the second research thrust of this thesis, the developed method-of-moments based estimation approach is extended to estimate the signal-to-noise ratio of PSK/QAM modulated signals in flat-fading channels, in which no a priori knowledge of the modulation format and channel parameters is assumed. Finally, in the third research thrust, a distributed spectrum sensing approach is proposed in which a network of radios collaboratively detects the presence, as well as the modulation scheme, of a signal through the use of a combination of cyclic spectrum feature-based signal classification and an iterative algorithm for optimal data fusion. / Master of Science

With the increasing advancements in the digital technology, future wireless systems are promising to support higher data rates, higher mobile speeds, and wider coverage areas, among other features. While further technological developments allow systems to support higher computational complexity, lower power consumption, and employ larger memory units, other resources remain limited. One such resource, which is of great importance to wireless systems, is the available spectrum for radio communications. To be able to support high data rate wireless applications, there is a need for larger bandwidths in the spectrum. Since the spectrum cannot be expanded, studies have been concerned with fully utilizing the available spectrum. One approach to achieve this goal is to reuse the available spectrum through space, time, frequency, and code multiplexing techniques. Another approach is to optimize the transceiver design as to achieve the highest throughput over the used spectrum. From the physical layer perspective, there is a need for a highly flexible and efficient modulation technique to carry the communication signal. A multicarrier modulation technique known as orthogonal frequency division multiplexing (OFDM) is one example of such a technique. OFDM has been used in a number of current wireless standards such as wireless fidelity (WiFi) and worldwide interoperability for microwave access (WiMAX) standards by the Institute of Electrical and Electronics Engineers (IEEE), and has been proposed for future 4G technologies such as the long term evolution (LTE) and LTE-advanced standards by the 3rd Generation Partnership Project (3GPP), and the wireless world initiative new radio (WINNER) standard by the Information society technologies (IST). This is due to OFDM’s high spectral efficiency, resistance to narrow band interference, support for high data rates, adaptivity, and scalability. In this dissertation, OFDM and multiuser OFDM , also known as orthogonal frequency division multiple access (OFDMA), techniques are investigated as a candidate for advanced wireless systems. Features and requirements of future applications are discussed in detail, and OFDM’s ability to satisfy these requirements is investigated. We identify a number of challenges that when addressed can improve the performance and throughput of OFDM-based systems. The challenges are investigated over three stages. In the first stage, minimizing, or avoiding, the interference between multiple OFDMA users as well as adjacent systems is addressed. An efficient algorithm for OFDMA uplink synchronization that maintains the orthogonality between multiple users is proposed. For adjacent channel interference, a new spectrum shaping method is proposed that can reduce the out-of-band radiation of OFDM signals. Both methods increase the utilization of available spectrum and reduce interference between different users. In the second stage, the goal is to maximize the system throughput for a given available bandwidth. The OFDM system performance is considered under practical channel conditions, and the corresponding bit error rate (BER) expressions are derived. Based on these results, the optimum pilot insertion rate is investigated. In addition, a new pilot pattern that improves the system ability to estimate and equalize various radio frequency (RF) impairments is proposed. In the last stage, acquiring reliable measurements regarding the received signal is addressed. Error vector magnitude (EVM) is a common performance metric that is being used in many of today’s standards and measurement devices. Inferring the signal-to-noise ratio (SNR) from EVM measurements has been investigated for either high SNR values or data-aided systems. We show that using current methods does not yield reliable estimates of the SNR under other conditions. Thus, we consider the relation between EVM and SNR for nondata-aided systems. We provide expressions that allow for accurate SNR estimation under various practical channel conditions.

Interference and jamming severely disrupt our ability to communicate by decreasing the effective signal-to-noise ratio and by making parameter estimation difficult at the receiver. The objective of this research work is to design robust wireless systems and algorithms to suppress the adverse effects of non-intentional co-channel interference (CCI) or intentional jamming. In particular, we develop chip-combining schemes with timing, channel, and noise-power estimation techniques, all of which mitigate CCI or jamming. We also exploit the spatial diversity and iterative receiver techniques for this purpose. Most of the existing timing estimation algorithms are robust against either large frequency offsets or CCI, but not against both at the same time. Hence, we develop a new frame boundary estimation method that is robust in the presence of severe co-channel interference and large carrier-frequency offsets. To solve the high peak-to-average-power ratio problem of a multicarrier code division multiple access (MC-CDMA) system and enhance its robustness against fading and jamming, we propose a constant-envelope MC-CDMA system employing cyclic delay diversity (CDD) as transmit diversity. We analyze the diversity order, coding gain, and bit-error rate upper bound. We also propose a blind, accurate, and computationally efficient signal-to-noise ratio estimator for the proposed system. We propose a configurable robust anti-jam receiver that estimates the frequency- or time-domain jammer state information (JSI) and uses it for chip combining in the corresponding domain. A soft-JSI-based chip-combining technique is proposed that outperforms conventional hard-JSI-based chip combining. We also derive a chip combiner that provides sufficient statistics to the decoder. Channel estimation is necessary for coherent signal detection and JSI estimation. Conversely, knowledge of the jamming signal power and JSI of different subcarriers can improve the accuracy of the channel estimates. Hence, we propose joint iterative estimation of the multiple-input multiple-output (MIMO) channel coefficients, jamming power, and JSI for a coded MC-CDMA MIMO system operating under jamming and a time-varying frequency-selective fading channel. Finally, we reduce the computational complexity of the JSI-based anti-jam receivers by introducing an expectation-maximization-based joint channel and noise-covariance estimator that does not need either the subcarrier JSI or the individual powers of the AWGN and jamming signal.