New approaches and algorithms are developed for the identification and estimation of low order models that represent multipath channel effects in Code Division Multiple Access (CDMA) communication systems. Based on these parsimonious channel models, low complexity receivers such as RAKE receivers are considered to exploit these propagation effects and enhance the system performance. We consider the scenario where multipath is frequency selective slowly fading and where the channel components including delays and attenuation coefficients are assumed to be constant over one or few signalling intervals. We model the channel as a long FIR-like filter (or a tapped delay line filter) with the number of taps related to the ratio between the channel delay-spread and the chip duration. Due to the high data rate of new CDMA systems, the channel length in terms of the chip duration will be very large. With classical channel estimation techniques this will result in poor estimates of many of the channel parameters where most of them are zero leading to a reduction in the system performance. Unlike classical techniques which estimate directly the channel response given the number of taps or given an estimate of the channel length, the proposed techniques in this work will firstly identify the significant multipath parameters using model selection techniques, then estimate these identified parameters. Statistical tests are proposed to determine whether or not each individual parameter is significant. A low complexity RAKE receiver is then considered based on estimates of these identified parameters only. The level of significance with which we will make this assertion will be controlled based on statistical tests such as multiple hypothesis tests. Frequency and time domain based approaches and model selection techniques are proposed to achieve the above proposed objectives. / The frequency domain approach for parsimonious channel estimation results in an efficient implementation of RAKE receivers in DS-CDMA systems. In this approach, we consider a training based strategy and estimate the channel delays and attenuation using the averaged periodogram and modified time delay estimation techniques. We then use model selection techniques such as the sphericity test and multiple hypotheses tests based on F-Statistics to identify the model order and select the significant channel paths. Simulations show that for a pre-defined level of significance, the proposed technique correctly identifies the significant channel parameters and the parsimonious RAKE receiver shows improved statistical as well as computational performance over classical methods. The time domain approach is based on the Bootstrap which is appropriate for the case when the distribution of the test statistics required by the multiple hypothesis tests is unknown. In this approach we also use short training data and model the channel response as an FIR filter with unknown length. Model parameters are then estimated using low complexity algorithms in the time domain. Based on these estimates, bootstrap based multiple hypotheses tests are applied to identify the non-zero coefficients of the FIR filter. Simulation results demonstrate the power of this technique for RAKE receivers in unknown noise environments. Finally we propose adaptive blind channel estimation algorithms for CDMA systems. Using only the spreading code of the user of interest and the received data sequence, four different adaptive blind estimation algorithms are proposed to estimate the impulse response of frequency selective and frequency non-selective fading channels. Also the idea is based on minimum variance receiver techniques. Tracking of a frequency selective varying fading channel is also considered. / A blind based hierarchical MDL model selection method is also proposed to select non-zero parameters of the channel response. Simulation results show that the proposed algorithms perform better than previously proposed algorithms. They have lower complexity and have a faster convergence rate. The proposed algorithms can also be applied to the design of adaptive blind channel estimation based RAKE receivers.

In wireless networks, communication links may be subject to random fatal impacts: for example, sensor networks under sudden power losses or cognitive radio networks with unpredictable primary user spectrum occupancy. Under such circumstances, it is critical to quantify how fast and reliably the information can be collected over attacked links. For a single point-to-point channel subject to a random attack, named as a dying channel, we model it as a block-fading (BF) channel with a finite and random channel length. First, we study the outage probability when the coding length K is fixed and uniform power allocation is assumed. Furthermore, we discuss the optimization over K and the power allocation vector PK to minimize the outage probability. In addition, we extend the single point to-point dying channel case to the parallel multi-channel case where each sub-channel is a dying channel, and investigate the corresponding asymptotic behavior of the overall outage probability with two different attack models: the independent-attack case and the m-dependent-attack case. It can be shown that the overall outage probability diminishes to zero for both cases as the number of sub-channels increases if the rate per unit cost is less than a certain threshold. The outage exponents are also studied to reveal how fast the outage probability improves over the number of sub-channels. Besides the information-theoretical results, we also study a practical coding scheme for the dying binary erasure channel (DBEC), which is a binary erasure channel (BEC) subject to a random fatal failure. We consider the rateless codes and optimize the degree distribution to maximize the average recovery probability. In particular, we first study the upper bound of the average recovery probability, based on which we define the objective function as the gap between the upper bound and the average recovery probability achieved by a particular degree distribution. We then seek the optimal degree distribution by minimizing the objective function. A simple and heuristic approach is also proposed to provide a suboptimal but good degree distribution.

This thesis contributes toward understanding fundamental limits of multi-user fading channels and random wireless networks. Specifically, considering different samples of channel gains corresponding to different users/nodes in a multi-user wireless system, the maximum number of channel gains supporting a minimum rate is asymptotically obtained. First, the user capacity of fading multi-user channels with minimum rates is analyzed. Three commonly used fading models, namely, Rayleigh, Rician and Nakagami are considered. For broadcast channels, a power allocation scheme is proposed to maximize the number of active receivers, for each of which, a minimum rate Rmin>0 can be achieved. Under the assumption of independent Rayleigh fading channels for different receivers, as the total number of receivers n goes to infinity, the maximum number of active receivers is shown to be arbitrarily close to ln(P.ln(n))/Rmin with probability approaching one, where P is the total transmit power. The results obtained for Rayleigh fading are extended to the cases of Rician and Nakagami fading models. Under the assumption of independent Rician fading channels for different receivers, as the total number of receivers n goes to infinity, the maximum number of active receivers is shown to be equal to ln(2P.ln(n))/Rmin with probability approaching one. For broadcast channels with Nakagami fading, the maximum number of active receivers is shown to be equal to ln(ω/μ.P.ln(n))/Rmin with probability approaching one, where ω and μ are the Nakagami distribution parameters. A by-product of the results is to also provide a power allocation strategy that maximizes the total throughput subject to the rate constraints. In multiple-access channels, the maximum number of simultaneous active transmitters (i.e. user capacity) is obtained in the many user case in which a minimum rate must be maintained for all active users. The results are presented in the form of scaling laws as the number of transmitters increases. It is shown that for all three fading distributions, the user capacity scales double logarithmically in the number of users and differs only by constants depending on the distributions. We also show that a scheduling policy that maximizes the number of simultaneous active transmitters can be implemented in a distributed fashion. Second, the maximum number of active links supporting a minimum rate is asymptotically obtained in a wireless network with an arbitrary topology. It is assumed that each source-destination pair communicates through a fading channel and destinations receive interference from all other active sources. Two scenarios are considered: 1) Small networks with multi-path fading, 2) Large Random networks with multi-path fading and path loss. In the first case, under the assumption of independent Rayleigh fading channels for different source-destination pairs, it is shown that the optimal number of active links is of the order log(N) with probability approaching one as the total number of nodes, N, tends to infinity. The achievable total throughput also scales logarithmically with the total number of links/nodes in the network. In the second case, a two-dimensional large wireless network is considered and it is assumed that nodes are Poisson distributed with a finite intensity. Under the assumption of independent multi-path fading for different source-destination pairs, it is shown that the optimal number of active links is of the order N with probability approaching one. As a result, the achievable per-node throughput obtained by multi-hop routing scales with Θ(1/√N).

This thesis contributes toward understanding fundamental limits of multi-user fading channels and random wireless networks. Specifically, considering different samples of channel gains corresponding to different users/nodes in a multi-user wireless system, the maximum number of channel gains supporting a minimum rate is asymptotically obtained. First, the user capacity of fading multi-user channels with minimum rates is analyzed. Three commonly used fading models, namely, Rayleigh, Rician and Nakagami are considered. For broadcast channels, a power allocation scheme is proposed to maximize the number of active receivers, for each of which, a minimum rate Rmin>0 can be achieved. Under the assumption of independent Rayleigh fading channels for different receivers, as the total number of receivers n goes to infinity, the maximum number of active receivers is shown to be arbitrarily close to ln(P.ln(n))/Rmin with probability approaching one, where P is the total transmit power. The results obtained for Rayleigh fading are extended to the cases of Rician and Nakagami fading models. Under the assumption of independent Rician fading channels for different receivers, as the total number of receivers n goes to infinity, the maximum number of active receivers is shown to be equal to ln(2P.ln(n))/Rmin with probability approaching one. For broadcast channels with Nakagami fading, the maximum number of active receivers is shown to be equal to ln(ω/μ.P.ln(n))/Rmin with probability approaching one, where ω and μ are the Nakagami distribution parameters. A by-product of the results is to also provide a power allocation strategy that maximizes the total throughput subject to the rate constraints. In multiple-access channels, the maximum number of simultaneous active transmitters (i.e. user capacity) is obtained in the many user case in which a minimum rate must be maintained for all active users. The results are presented in the form of scaling laws as the number of transmitters increases. It is shown that for all three fading distributions, the user capacity scales double logarithmically in the number of users and differs only by constants depending on the distributions. We also show that a scheduling policy that maximizes the number of simultaneous active transmitters can be implemented in a distributed fashion. Second, the maximum number of active links supporting a minimum rate is asymptotically obtained in a wireless network with an arbitrary topology. It is assumed that each source-destination pair communicates through a fading channel and destinations receive interference from all other active sources. Two scenarios are considered: 1) Small networks with multi-path fading, 2) Large Random networks with multi-path fading and path loss. In the first case, under the assumption of independent Rayleigh fading channels for different source-destination pairs, it is shown that the optimal number of active links is of the order log(N) with probability approaching one as the total number of nodes, N, tends to infinity. The achievable total throughput also scales logarithmically with the total number of links/nodes in the network. In the second case, a two-dimensional large wireless network is considered and it is assumed that nodes are Poisson distributed with a finite intensity. Under the assumption of independent multi-path fading for different source-destination pairs, it is shown that the optimal number of active links is of the order N with probability approaching one. As a result, the achievable per-node throughput obtained by multi-hop routing scales with Θ(1/√N).

Adaptive modulation and diversity combining represent very important adaptive solutions for future generations of wireless communication systems. Indeed, to improve the performance and the efficiency of these systems, these two techniques recently have been used jointly in new schemes named joint adaptive modulation and diversity combining (JAMDC) schemes. Considering the problem of finding lowcomplexity, bandwidth-efficient, and processing-power efficient transmission schemes for a downlink scenario and capitalizing on some of these recently proposed JAMDC schemes, we propose and analyze three fully joint adaptive modulation, diversity combining, and power control (FJAMDC) schemes. More specifically, the modulation constellation size, the number of combined diversity paths, and the needed power level are determined jointly to achieve the highest spectral efficiency with the lowest possible combining complexity, given the fading channel conditions and the required bit error rate (BER) performance. The performance of these three FJAMDC schemes is analyzed in terms of their spectral efficiency, processing power consumption, and error-rate performance. Selected numerical examples show that these schemes considerably increase the spectral efficiency of the existing JAMDC schemes with a slight increase in the average number of combined paths for the low signal to noise ratio range while maintaining compliance with the BER performance and a low radiated power resulting in a substantial decrease in interference to co-existing systems/users.

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.

Most of the conventional communication systems use channel interleaving as well as hard decision decoding in their designs, which lead to discarding channel memory and soft-decision information. This simplification is usually done since the complexity of handling the memory or soft-decision information is rather high. In this work, we design two lossy joint source-channel coding (JSCC) schemes that do not use explicit algebraic channel coding for a recently introduced channel model, in order to take advantage of both channel memory and soft-decision information. The channel model, called the non-binary noise discrete channel with queue based noise (NBNDC-QB), obtains closed form expressions for the channel transition distribution, correlation coefficient, and many other channel properties. The channel has binary input and $2^q$-ary output and the noise is a $2^q$-ary Markovian stationary ergodic process, based on a finite queue, where $q$ is the output's soft-decision resolution. We also numerically show that the NBNDC-QB model can effectively approximate correlated Rayleigh fading channels without losing its analytical tractability. The first JSCC scheme is the so called channel optimized vector quantizer (COVQ) and the second scheme consists of a scalar quantizer, a proper index assignment, and a sequence maximum a posteriori (MAP) decoder, designed to harness the redundancy left in the quantizer's indices, the channel's soft-decision output, and noise time correlation. We also find necessary and sufficient condition when the sequence MAP decoder is reduced to an instantaneous symbol-by-symbol decoder, i.e., a simple instantaneous mapping. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2011-09-25 19:43:28.785

abstract: Distributed inference has applications in fields as varied as source localization, evaluation of network quality, and remote monitoring of wildlife habitats. In this dissertation, distributed inference algorithms over multiple-access channels are considered. The performance of these algorithms and the effects of wireless communication channels on the performance are studied. In a first class of problems, distributed inference over fading Gaussian multiple-access channels with amplify-and-forward is considered. Sensors observe a phenomenon and transmit their observations using the amplify-and-forward scheme to a fusion center (FC). Distributed estimation is considered with a single antenna at the FC, where the performance is evaluated using the asymptotic variance of the estimator. The loss in performance due to varying assumptions on the limited amounts of channel information at the sensors is quantified. With multiple antennas at the FC, a distributed detection problem is also considered, where the error exponent is used to evaluate performance. It is shown that for zero-mean channels between the sensors and the FC when there is no channel information at the sensors, arbitrarily large gains in the error exponent can be obtained with sufficient increase in the number of antennas at the FC. In stark contrast, when there is channel information at the sensors, the gain in error exponent due to having multiple antennas at the FC is shown to be no more than a factor of 8/π for Rayleigh fading channels between the sensors and the FC, independent of the number of antennas at the FC, or correlation among noise samples across sensors. In a second class of problems, sensor observations are transmitted to the FC using constant-modulus phase modulation over Gaussian multiple-access-channels. The phase modulation scheme allows for constant transmit power and estimation of moments other than the mean with a single transmission from the sensors. Estimators are developed for the mean, variance and signal-to-noise ratio (SNR) of the sensor observations. The performance of these estimators is studied for different distributions of the observations. It is proved that the estimator of the mean is asymptotically efficient if and only if the distribution of the sensor observations is Gaussian. / Dissertation/Thesis / Ph.D. Electrical Engineering 2010

Tato diplomová práce se zabývá analýzou, návrhem a simulací modelu fyzické vrstvy bezdrátového komunikačního systému IEEE 802.11af. V práci je především popsána vysílací část komunikačního systému s důrazem na zpracování IEEE 802.11af signálu. Následně je vytvořeno blokové schéma a model pro vysílací a přijímací části ve vysílacích módech SISO a MIMO. Model je realizován s grafickým uživatelským rozhraním v programovém prostředí MATLAB. Vytvořená aplikace slouží k prozkoumání vlastností IEEE 802.11af modelu na základě jeho systémových parametrů. Systémové parametry jsou volitelné uživatelem a aplikace poskytuje možnost simulace různých přenosových scénářů.

This Master thesis is focused on detailed description of the DVB-T2 system. This work deals with the description of the particular parts of models and with typical RF transmission channels for fixed and mobile reception. In order to simulate the impact of the fading transmission channels on the transmitted signal there was developed an appropriate application in MATLAB. The graphic user interface of this application allows set the transmission parameters of DVB-T2 and the parameters of the transmission channels. Results of simulations with various settings are evaluated and compared with the results, obtained from the DVB-T measurements.