Transmission resource allocation in multi-antenna wireless communication systems with channel uncertainty

In this thesis we investigate the design of transmission resource allocation in current and future wireless communication systems. We focus on systems with multiple antennas and characterize their performance from an information-theoretic viewpoint. The goal of this work is to provide practical transmission and resource allocation strategies taking into account imperfections in estimating the wireless channel, as well as the broadcast nature of the wireless channel. In the first part of the thesis, we consider training-based transmission schemes in which pilot symbols are inserted into data blocks to facilitate channel estimation. We consider one-way training-based systems with and without feedback, as well as two-way training-based systems. Two-way training enables both the transmitter and the receiver to obtain the channel state information (CSI) through reverse training and forward training, respectively. In all considered cases, we derive efficient strategies for transmit time and/or energy allocation among the pilot and data symbols. These strategies usually have analytical closed-form expressions and can achieve near optimal capacity performance evidenced by extensive numerical analysis. In one-way training-based systems without feedback, we consider both spatially independent and correlated channels. For spatially independent channels, we provide analytical bounds on the optimal training length and study the optimal antenna con¯guration that maximizes an ergodic capacity lower bound. For spatially correlated channels, we provide simple pilot and data transmission strategies that are robust under least-favorable channel correlation conditions. In one-way training-based systems with feedback, we study channel gain feedback (CGF), channel covariance feedback (CCF) and hybrid feedback. For spatially independent channels with CGF, we show that the solutions to the optimal training length and energy coincide with those for systems without feedback. For spatially correlated channels with CCF, we propose a simple transmission scheme, taking into account the fact that the optimal training length is at most as large as the number of transmit antennas. We then provided solution to the optimal energy allocation between pilot and data transmissions, which does not depend on the channel spatial correlation under a mild condition. Our derived resource allocation strategies in CGF and CCF systems are extended to hybrid CCF-CGF systems. In two-way training-based systems, we provide analytical solutions to the transmit power distribution among the different training phases and the data transmission phase. These solutions are shown to have near optimal symbol error rate (SER) and capacity performance. We find that the use of two-way training can provide noticeable performance improvement over reverse training only when the system is operating at moderate to high signal-to-noise ratio (SNR) and using high-order modulations. While this improvement from two-way training is insignificant at low SNR or low-order modulations. In the second part of the thesis, we consider transmission resource allocation in security-constrained systems. Due to the broadcast nature of the wireless medium, security is a fundamental issue in wireless communications. To guarantee secure communication in the presence of eavesdroppers, we consider a multi-antenna transmission strategy which sends both an information signal to the intended receiver and a noise-like signal isotropically to confuse the eavesdroppers. We study the optimal transmit power allocation between the information signal and the artificial noise. In particular, we show that equal power allocation is a near optimal strategy for non-colluding eavesdroppers, while more power should be used to generate the artificial noise for colluding eavesdroppers. In the presence of channel estimation errors, we find that it is better to create more artificial noise than to increase the information signal strength

Performance Analysis of Arbitrarily-Shaped Underlay Cognitive Networks: Effects of Secondary User Activity Protocols

This paper analyzes the performance of the primary and secondary users (SUs) in an arbitrarily-shaped underlay cognitive network. In order to meet the interference threshold requirement for a primary receiver (PU-Rx) at an arbitrary location, we consider different SU activity protocols which limit the number of active SUs. We propose a framework, based on the moment generating function (MGF) of the interference due to a random SU, to analytically compute the outage probability in the primary network, as well as the average number of active SUs in the secondary network. We also propose a cooperation-based SU activity protocol in the underlay cognitive network which includes the existing threshold-based protocol as a special case. We study the average number of active SUs for the different SU activity protocols, subject to a given outage probability constraint at the PU and we employ it as an analytical approach to compare the effect of different SU activity protocols on the performance of the primary and secondary networks.Comment: submitted to possible IEEE Transactions publicatio

Covert Communication in Fading Channels under Channel Uncertainty

A covert communication system under block fading channels is considered where users experience uncertainty about their channel knowledge. The transmitter seeks to hide the covert communication to a private user by exploiting a legitimate public communication link while the warden tries to detect this covert communication by using a radiometer. We derive the exact expression for the radiometers optimal threshold which determines the performance limit of the wardens detector. Furthermore for given transmission outage constraints the achievable rates for legitimate and covert users are analyzed while maintaining a specific level of covertness. Our numerical results illustrate how the achievable performance is affected by the channel uncertainty and required level of covertness.Comment: to appear in IEEE VTC2017-Sprin

Optimal Compression and Transmission Rate Control for Node-Lifetime Maximization

We consider a system that is composed of an energy constrained sensor node and a sink node, and devise optimal data compression and transmission policies with an objective to prolong the lifetime of the sensor node. While applying compression before transmission reduces the energy consumption of transmitting the sensed data, blindly applying too much compression may even exceed the cost of transmitting raw data, thereby losing its purpose. Hence, it is important to investigate the trade-off between data compression and transmission energy costs. In this paper, we study the joint optimal compression-transmission design in three scenarios which differ in terms of the available channel information at the sensor node, and cover a wide range of practical situations. We formulate and solve joint optimization problems aiming to maximize the lifetime of the sensor node whilst satisfying specific delay and bit error rate (BER) constraints. Our results show that a jointly optimized compression-transmission policy achieves significantly longer lifetime (90% to 2000%) as compared to optimizing transmission only without compression. Importantly, this performance advantage is most profound when the delay constraint is stringent, which demonstrates its suitability for low latency communication in future wireless networks.Comment: accepted for publication in IEEE Transactions on Wireless Communicaiton

Training-Based SWIPT: Optimal Power Splitting at the Receiver

We consider a point-to-point system with simultaneous wireless information and power transfer (SWIPT) over a block fading channel. Each transmission block consists of a training phase and a data transmission phase. Pilot symbols are transmitted during the training phase for channel estimation at the receiver. To enable SWIPT, the receiver adopts a power-splitting design, such that a portion of the received signal is used for channel estimation or data detection, while the remaining is used for energy harvesting. We optimally design the power-splitting ratios for both training and data phases to achieve the best ergodic capacity performance while maintaining a required energy harvesting rate. Our result shows how a power-splitting receiver can make the best use of the received pilot and data signals to obtain the optimal SWIPT performance.ARC Discovery Projects Grant DP14010113