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Power Control and Resource Allocation for QoS-Constrained Wireless Networks
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.Cambridge Overseas Trust; China Scholarship Counci
Coding for Cooperative Communications
The area of cooperative communications has received tremendous research interest
in recent years. This interest is not unwarranted, since cooperative communications
promises the ever-so-sought after diversity and multiplexing gains typically
associated with multiple-input multiple-output (MIMO) communications, without
actually employing multiple antennas. In this dissertation, we consider several cooperative
communication channels, and for each one of them, we develop information
theoretic coding schemes and derive their corresponding performance limits. We next
develop and design practical coding strategies which perform very close to the information
theoretic limits.
The cooperative communication channels we consider are: (a) The Gaussian relay
channel, (b) the quasi-static fading relay channel, (c) cooperative multiple-access
channel (MAC), and (d) the cognitive radio channel (CRC). For the Gaussian relay
channel, we propose a compress-forward (CF) coding strategy based on Wyner-Ziv
coding, and derive the achievable rates specifically with BPSK modulation. The CF
strategy is implemented with low-density parity-check (LDPC) and irregular repeataccumulate
codes and is found to operate within 0.34 dB of the theoretical limit. For
the quasi-static fading relay channel, we assume that no channel state information
(CSI) is available at the transmitters and propose a rateless coded protocol which
uses rateless coded versions of the CF and the decode-forward (DF) strategy. We
implement the protocol with carefully designed Raptor codes and show that the implementation suffers a loss of less than 10 percent from the information theoretical limit. For
the MAC, we assume quasi-static fading, and consider cooperation in the low-power
regime with the assumption that no CSI is available at the transmitters. We develop
cooperation methods based on multiplexed coding in conjunction with rateless
codes and find the achievable rates and in particular the minimum energy per bit to
achieve a certain outage probability. We then develop practical coding methods using
Raptor codes, which performs within 1.1 dB of the performance limit. Finally, we
consider a CRC and develop a practical multi-level dirty-paper coding strategy using
LDPC codes for channel coding and trellis-coded quantization for source coding. The
designed scheme is found to operate within 0.78 dB of the theoretical limit.
By developing practical coding strategies for several cooperative communication
channels which exhibit performance close to the information theoretic limits, we show
that cooperative communications not only provide great benefits in theory, but can
possibly promise the same benefits when put into practice. Thus, our work can be
considered a useful and necessary step towards the commercial realization of cooperative
communications
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