Developments such as machine-to-machine communications and multimedia services are placing growing demands on high-speed reliable transmissions and limited wireless spectrum resources. Although multiple-input multiple-output (MIMO) systems have shown the ability to provide reliable transmissions in fading channels, it is not practical for single-antenna devices to support MIMO system due to cost and hardware limitations. Cooperative communication allows single-antenna devices to share their spectrum resources and form a virtual MIMO system where their quality of service (QoS) may be improved via cooperation. Most cooperative communication solutions are based on fixed spectrum access schemes and thus cannot further improve spectrum efficiency. In order to support more users in the existing spectrum, we consider dynamic spectrum access schemes and cognitive radio techniques in this dissertation. Our work includes the modelling, characterization and optimization of QoS-constrained cooperative networks and cognitive radio networks. QoS constraints such as delay and data rate are modelled. To solve power control and channel resource allocation problems, dynamic power control, matching theory and multi-armed bandit algorithms are employed in our investigations. In this dissertation, we first consider a cluster-based cooperative wireless network utilizing a centralized cooperation model. The dynamic power control and optimization problem is analyzed in this scenario. We then consider a cooperative cognitive radio network utilizing an opportunistic spectrum access model. Distributed spectrum access algorithms are proposed to help secondary users utilize vacant channels of primary users in order to optimize the total utility of the network. Finally, a noncooperative cognitive radio network utilizing the opportunistic spectrum access model is analyzed. In this model, primary users do not communicate with secondary users. Therefore, secondary users are required to find vacant channels on which to transmit. Multi-armed bandit algorithms are proposed to help secondary users predict the availability of licensed channels. In summary, in this dissertation we consider both cooperative communication networks and cognitive radio networks with QoS constraints. Efficient power control and channel resource allocation schemes have been proposed for optimization problems in different scenarios.

We consider single-source single-sink (ss-ss) multi-hop relay networks, with slow-fading links and single-antenna half-duplex relay nodes. While two-hop cooperative relay networks have been studied in great detail in terms of the diversity-multiplexing tradeoff (DMT), few results are available for more general networks. In this paper, we identify two families of networks that are multi-hop generalizations of the two-hop network: K-Parallel-Path (KPP) networks and layered networks. KPP networks can be viewed as the union of K node-disjoint parallel relaying paths, each of length greater than one. KPP networks are then generalized to KPP(I) networks, which permit interference between paths and to KPP(D) networks, which possess a direct link from source to sink. We characterize the DMT of these families of networks completely for K > 3. Layered networks are networks comprising of layers of relays with edges existing only between adjacent layers, with more than one relay in each layer. We prove that a linear DMT between the maximum diversity dmax and the maximum multiplexing gain of 1 is achievable for single-antenna fully-connected layered networks. This is shown to be equal to the optimal DMT if the number of relaying layers is less than 4. For multiple-antenna KPP and layered networks, we provide an achievable DMT, which is significantly better than known lower bounds for half duplex networks. For arbitrary multi-terminal wireless networks with multiple source-sink pairs, the maximum achievable diversity is shown to be equal to the min-cut between the corresponding source and the sink, irrespective of whether the network has half-duplex or full-duplex relays. For arbitrary ss-ss single-antenna directed acyclic networks with full-duplex relays, we prove that a linear tradeoff between maximum diversity and maximum multiplexing gain is achievable. Along the way, we derive the optimal DMT of a generalized parallel channel and derive lower bounds for the DMT of triangular channel matrices, which are useful in DMT computation of various protocols. All protocols in this paper are explicit and use only amplify-and-forward (AF) relaying. We also construct codes with short block-lengths based on cyclic division algebras that achieve the optimal DMT for all the proposed schemes. Two key implications of the results in the paper are that the half-duplex constraint does not entail any rate loss for a large class of cooperative networks and that simple AF protocols are often sufficient to attain the optimal DMT.

In this thesis, we consider a cooperative relay-assisted communication system that uses rateless codes. When multiple relays are present, the relay with the highest channel gain to the source is the first to successfully decode a message from the source and forward it to the destination. Thus, the unique properties of rateless codes ensure that both rate adaptation and relay selection occur without the transmitting source or relays acquiring instantaneous channel knowledge. We show that in such cooperative systems, buffering messages at relays significantly increases throughput. We develop a novel analysis of these systems that combines the communication-theoretic aspects of cooperation over fading channels with the queuing-theoretic aspects associated with buffering. Closed-form expressions are derived for the throughput and end-to-end delay for the general case in which the channels between various nodes are not statistically identical. Results are also shown for the benchmark system that does not buffer messages. Though relay selection combined with buffering of messages at the relays substantially increases the throughput of a cooperative network, it also increases the end-to-end delays due to the additional queuing delays at the relay nodes. In order to overcome this, we propose a novel method that exploits a unique property of rateless codes that enables a receiver to decode a message from non-contiguous and unordered portions of the received signal. In it, each relay, depending on its queue length, ignores its received coded bits with a given probability. We show that this substantially reduces the end-to-end delays while retaining almost all of the throughput gain achieved by buffering. In effect, the method increases the odds that the message is first decoded by a relay with a smaller queue. Thus, the queuing load is balanced across the relays and traded off with transmission times. We derive conditions for the stability of this system when the various channels undergo fading. Despite encountering analytically intractable G/GI/1 queues in our system, we also gain insights about the method by analyzing a similar system with a simpler model for the relay-to-destination transmission times. Next we combine the single relay selection scheme at the source with physical layer power control at the relays (due to the diversity provided by the rateless codes, power control at the source is not needed). We derive an optimal power control policy that minimizes the relay to destination transmission time. Due to its computational and implementation complexity, we develop another heuristic easily implementable near optimal policy. In this policy, power allocated turns out to be inversely proportional to the square root of channel gain. We also see that this policy performs better than the channel inversion policy. Our power control solution substantially decreases the mean end-to-end delays with a marginal increase in throughput also. Finally, we combine bit dropping with power control at the relays which further improves the system performance.