This thesis presents packet-level channel modeling, spectrum efficiency optimization and channel estimation for wireless cooperative communication systems with diversity combining. Cooperative transmission in a wireless network allows neighboring nodes to share their communication resources to create a virtual antenna array by distributed transmission and signal processing, which is useful to exploit spatial diversity, increase channel capacity, and attain wider service coverage with single-antenna terminals. How to exploit spatial diversity and leverage the multi-hop channel structure is an important research issue for the cooperative network. In this thesis, two cooperative schemes are considered, amplify and forward (AF) and demodulation and forward (DMF). For AF cooperative systems, finite state Markov chain (FSMC) models are designed in analyzing the system performance considering time-varying channel behaviors and facilitating fast channel simulation. For DMF cooperative systems, first we formulate the optimization problem that jointly chooses the modulation schemes at the source and relay nodes, to maximize the throughput of cooperative systems under the BER constraint. Second, we propose to use the soft values of each bit to devise a simple and effective combining scheme, which can be applied for both AF and DMF cooperative systems. Third, as the soft values from demodulation process can also be used for measuring the channel estimation accuracy, a soft value-assisted channel estimation has been proposed by iteratively utilizing soft values to refine the accurate channel estimation. In addition, we also implement the soft value module in OFDM-based transceiver system based on a GNU Radio/USRP2 platform, and verify the effectiveness and performance improvement for the proposed SVC systems. As considering wireless cooperative systems has attracted increasing attentions from both academic and industry to meet the demanding of the high data rate transmission, the packet-level channel modeling, adaptive modulation, spectrum efficiency improvement frameworks based on soft value combining and accurate channel estimation algorithms proposed in this thesis are essential for future proliferation of high data rate, reliable and efficient wireless communication networks. / Graduate / 0537 / 0544 / 0984

The demand for access to information when and where you need has motivated the transition of wireless communications from a fixed infrastructure based cellular communications technology to a more pervasive adhoc wireless networking technology. Challenges still remain in wireless adhoc networks in terms of meeting higher capacity demands, improved reliability and longer connectivity before it becomes a viable widespread commercial technology. Present day wireless mesh networking uses node-to-node serial multi-hop communication to convey information from source to destination in the network. The performance of such a network depends on finding the best possible route between the source and destination nodes. However the end-to-end performance can only be as good as the weakest link within a chosen route. Unlike wired networks, the quality of point-to-point links in a wireless mesh network is subject to random fluctuations. This adversely affects the performance resulting in poor throughput and poor energy efficiency. In recent years, a new paradigm for communication called cooperative communications has been proposed for which initial information theoretic studies have shown the potential for improvements in capacity over traditional multi-hop wireless networks. Cooperative communication involves exploiting the broadcast nature of the wireless medium to form virtual antenna arrays out of independent single-antenna network nodes for transmission. In this research we explore the fundamental performance limits of cooperative communication under more practical operating scenarios. Specifically we provide a framework for computing the outage and ergodic capacities of non identical distributed MIMO links, study the effect of time synchronization error on system performance, analyze the end-to-end average bit error rate (ABER) performance under imperfect relaying, and study range extension and energy efficiency offered by the system when compared to a traditional system. / Ph. D.

Dynamic spectrum access (DSA) is a promising approach to alleviate spectrum scarcity and improve spectrum utilization. Our work aims to enhance the utilization of the available white spaces in the licensed spectrum by enabling cooperative communication in the secondary networks. We investigate the ability of a two-hop cooperative transmission to reduce the effect of primary user interruption on secondary transmissions. We analyze the performance of a cooperative secondary transmission by modeling the interaction between primary user and secondary user transmissions using a discrete time Markov chain (DTMC). The analysis shows a significant enhancement in the secondary transmission efficiency and throughput when cooperative transmission is utilized compared to that of direct transmission, especially at high levels of primary user activity. We extend our study to model secondary cooperative transmission in realistic scenarios. We evaluate the throughput performance enhancement in the secondary infrastructure network analytical and by simulation. A simple scenario is modeled analytically by a DTMC that captures the probability of finding intermediate relays according to nodes' density and by discrete event simulation where both results confined each other. We introduce a dedicated cooperative and cognitive Media Access Control (MAC) protocol named CO2MAC to facilitate secondary users transmissions in infrastructure-based secondary networks. The proposed MAC enables utilizing cooperative Multi-Input-Multi-Output (MIMO) transmission techniques to further enhance the throughput performance. By using the proposed MAC, we quantify the enhancement in the throughput of secondary infrastructure networks via simulation for complex scenarios. The results show an enhancement in cooperative transmission throughput compared to that of direct transmission, especially at crowded spectrum due to the ability of cooperative transmissions to reduce the negative effect of primary user interruptions by buffering the data at intermediate relays. Also, the cooperative throughput performance enhances compared to that of direct transmission as the nodes' density increases due to the increase in the probability of finding intermediate relays. After that, we answer two questions. The first question is about the way a secondary user pays the cooperation price to its relay and what are the conditions under which the cooperation is beneficial for both of them. The second question is about how to pair the cooperating nodes and allocate channels in an infrastructure based secondary network. To answer the first question, we model the cooperation between the secondary user and its relay as a resource exchange process, where the secondary user vacates part of its dedicated free spectrum access time to the relay as a price for the energy consumed by the relay in forwarding the secondary user's packets. We define a suitable utility function that combines the throughput and the energy then we apply axiomatic bargaining solutions, namely Nash bargaining solution (NBS) and egalitarian bargaining solution (EBS) to find the new free spectrum access shares for the secondary user and the relay based on the defined utility in the cooperation mode. We show that under certain conditions, the cooperation is beneficial for both the secondary user and the relay where both achieve a higher utility and throughput compared to the non-cooperative mode. Finally, based on the bargaining based shares of the cooperating nodes, the node pairing and channel allocation are optimized for different objectives, namely maximizing the total network throughput or minimizing the maximum unsatisfied demand. Our bargaining based framework shows a comparable performance with the case when the nodes' free spectrum access time shares are jointly optimized with the pairing and allocation process, at the same time, our cooperation framework provides an incentive reward for the secondary users and the relays to involve in cooperation by giving every node a share of the free spectrum that proportional to its utility. We also study the case of using multiple secondary access points which gives more flexibility in node pairing and channel allocation and achieves a better performance in terms of the two defined objectives. / Ph. D.

This dissertation studies several problems centered around developing a better understanding of the energy efficiency of cooperative wireless communication systems. Cooperative communication is a technique where two or more nodes in a wireless network pool their antenna resources to form a "virtual antenna array". Over the last decade, researchers have shown that many of the benefits of real antenna arrays, e.g. spatial diversity, increased range, and/or decreased transmission energy, can be achieved by nodes using cooperative transmission. This dissertation extends the current body of knowledge by providing a comprehensive study of the energy efficiency of two-source cooperative transmission under differing assumptions about channel state knowledge, cooperative protocol, and node selfishness. The first part of this dissertation analyzes the effect of channel state information on the optimum energy allocation and energy efficiency of a simple cooperative transmission protocol called "orthogonal amplify-and-forward" (OAF). The source nodes are required to achieve a quality-of service (QoS) constraint, e.g. signal to noise ratio or outage probability, at the destination. Since a QoS constraint does not specify a unique transmit energy allocation when the nodes use OAF cooperative transmission, minimum total energy strategies are provided for both short-term and long-term QoS constraints. For independent Rayleigh fading channels, full knowledge of the channel state at both of the sources and at the destination is shown to significantly improve the energy efficiency of OAF cooperative transmission as well as direct (non-cooperative) transmission. The results also demonstrate how channel state knowledge affects the minimum total energy allocation strategy. Under identical channel state knowledge assumptions, the results demonstrate that OAF cooperative transmission tends to have better energy efficiency than direct transmission over a wide range of channel conditions. The second part of this dissertation focuses on the development of an opportunistic hybrid cooperative transmission protocol that achieves increased energy efficiency by not only optimizing the resource allocation but also by selecting the most energy efficient cooperative transmission protocol from a set of available protocols according to the current channel state. The protocols considered in the development of the hybrid cooperative transmission protocol include compress-and-forward (CF), estimate-and-forward (EF), non-orthogonal amplify-and-forward (NAF), and decode-and-forward (DF). Instantaneous capacity results are analyzed under the assumption of full channel state knowledge at both of the sources and the destination node. Numerical results are presented showing that the delay limited capacity and outage probability of the hybrid cooperative transmission protocol are superior to that of any single protocol and are also close to the cut-set bound over a wide range of channel conditions. The final part of this dissertation focuses on the issue of node selfishness in cooperative transmission. It is common to assume in networks with a central authority, e.g. military networks, that nodes will always be willing to offer help to other nodes when requested to do so. This assumption may not be valid in ad hoc networks operating without a central authority. This section of the dissertation considers the effect selfish behavior on the energy efficiency of cooperative communication systems. Using tools from non-cooperative game theory, a two-player relaying game is formulated and analyzed in non-fading and fading channel scenarios. In non-fading channels, it is shown that a cooperative equilibrium can exist between two self-interested sources given that the end of the cooperative interaction is uncertain, that the sources can achieve mutual benefit through cooperation, and that the sources are sufficiently patient in the sense that they value future payoffs. In fading channels, a cooperative conditional trigger strategy is proposed and shown to be an equilibrium of the two-player game. Sources following this strategy are shown to achieve an energy efficiency very close to that of a centrally-controlled system when they are sufficiently patient. The results in this section show that cooperation can often be established between two purely self-interested sources without the development of extrinsic incentive mechanisms like virtual currency.

We consider the problem of allocating resources in large wireless net- works in which multiple information flows must be accommodated. In particular, we seek a method for selecting schedules, routes, and power allocations for networks with terminals capable of user-cooperation at the signal level. To that end, we adopt a general information-theoretic communications model, in which the datarate of a wireless link is purely a function of transmission power, pathloss and interference. We begin by studying the case of resource allocation when only point-to-point links are available. The problem is NP-hard in this case, requiring an exponentially-complex exhaustive search to guarantee an optimal solution. This is prohibitively difficult for anything but the smallest of networks, leading us to approximate the problem using a decomposition approach. We construct the solution iteratively, developing polynomial-time algorithms to optimally allocate resources on a per-frame basis. We then update the network graph to reflect the resources consumed by the allocated frame. To manage this decomposition, we present a novel tool, termed the Network-Flow Interaction Chart. By representing the network in both space and time, our techniques trade off interference with throughput for each frame, offering considerable performance gains over schemes of similar complexity. Recognizing that our approach requires a large amount of overhead, we go on to develop a method in which it may be decentralized. We find that while the overhead is considerably lower, the limited solution space results in suboptimal solutions in a throughput sense. We conclude with a generalization of the Network-Flow Interaction Chart to address cooperative resource allocation. We represent cooperative links using "metanodes," which are made available to the allocation algorithms alongside point-to-point links and will be selected only if they offer higher throughput. The data-carrying capability of the cooperative links is modeled using Decode-and-Forward achievable rates, which are functions of transmit power and interference, and so may be incorporated directly into our framework. We demonstrate that allocations incorporating cooperation results in significant performance gains as compared to using point-to-point links alone.

Grice (1982) and Bar-On and Green (2010) each provide 'continuity stories' which attempt to explain how a human-like language could emerge from the primitive communication practices of non-human animals. I offer desiderata for a proper account of linguistic continuity in order to argue that these previous accounts fall short in important ways. I then introduce the recent evolutionary literature on non-cooperative communication in order to construct a continuity story which better satisfies the proposed desiderata while retaining the positive aspects of the proposals of Grice and Bar-On and Green. The outcome of this project is a more tenable and empirically investigable framework chronicling the evolution of human-like language from communicative abilities currently found in non-human animals.

In this paper, we consider the code division multiple access of the multiuser cooperative network system, all sources transmit signals using assigned spreading waveforms in first phase, and all relays transmit precoded signals using a common spreading waveform to help send signals to all destinations in second phase, in order to improve the performance. In this paper, we proposed the precoding strategy of relay point and the decoding strategy of destination point; at first we use the zero-forcing to eliminate the multi-user interferen- ce at the destination, and then joint design of the precoding vector at relay point and the decoding vector at destination point to achieve different optimization objectives. In this paper, we consider the power constraints to optimal the average SNR for the precoding vector and decoding vector, but the precoding vector favors the source-destination pairs with better channel quality in this condition, we also present the design of fairness, joint design of the precoding vector and the decoding vector to make the worst SNR can have the best signal-to-noise ratio after the design, and also consider the power constrain.

Cooperative communication has been shown that it is an effective way to combat the outage caused by channel fading; that is, it provides the spatial diversity for communication. Except for amplify-and-forward (AF) and decode-and-forward (DF), compressed-and-forward (CF) is also an efficient forwarding strategy. In this thesis, we proposed a new CF scheme. In the existing CF protocol, the relay will switch to the DF mode when the source transmitted signal can be recovered by the relay completely; no further compression is made in this scheme. In our proposed, the relay will estimate if the codeword in a block is succeeded decoded, choose the corresponding forwarding methods with LDPC coding; those are based on joint source-channel coding or compressive sensing. At the decode side, a joint decoder with side information that performs sum-product algorithm (SPA) to decode the source message. Simulation results show that the proposed CF scheme can acquire the spatial diversity and outperform AF and DF schemes.

In this paper, the channel estimation problem for a two-way relay network (TWRN) based on two different wireless channel assumptions is considered. Previous works have proposed a training-based channel estimation method to obtain the channel state information (CSI). But in practice the channel change from one data block to another, which may cause the performance degradation due to the outdated CSI. To enhance the performance, the system has to insert more training signal. In order to improve the bandwidth efficiency, we propose a joint channel estimation and data detection method based on expectation-maximization (EM) algorithm. From the simulation results, the proposed method can combat the effect of fading channel and still the MSE results are very close to Cramer-Rao Lower Bound (CRLB) at the high signal-to-noise ratio (SNR) region. Additionally, as compare with the previous work, the proposed scheme also has a better detection performance for both time-varying and time-invariant channels.

For wireless communication systems, due to broadcasting nature of wireless medium, how to keep eavesdroppers from wiretapping messages is worth investigated. In addition to encryption techniques applied in application layer, physical layer secrecy techniques have been studied in literature. Under the premise that eavesdropper cannot steal any information, physical layer secrecy focus on maximizing the capacity of legal transmission, and make it more reliable by using physical properties of wireless channel. This thesis considers an amplify-and-forward (AF) multiple-input multiple-output (MIMO) cooperative communication network with an untrusted relay (UR), and linear precoders are employed at source, relay, and destination. The relay here serves as a bridge of transmission 1 between the source and the destination. However, assume that the untrusted relay may wiretap information from the source without authorization. In order to prevent relay from wiretapping information, the destination generates artificial noise (AN) to interfere the relay, when the relay is receiving information from the source. Since AN is generated by the destination, the destination can eliminate AN by itself after receiving signal from the relay without corrupting signals of legal transmission. We propose precoder design for source, relay and destination to maximize secrecy capacity under the power constraint of three nodes. By utilizing singular value decomposition (SVD) of all channel matrices and Hadamard inequality, we simplify the optimization problem of precoding matrices to scalar optimization problem, and optimization can be accomplished recursively.