Linear Precoders for Non-Regenerative Asymmetric Two-way Relaying in Cellular Systems

Two-way relaying (TWR) reduces the spectral-efficiency loss caused in conventional half-duplex relaying. TWR is possible when two nodes exchange data simultaneously through a relay. In cellular systems, data exchange between base station (BS) and users is usually not simultaneous e.g., a user (TUE) has uplink data to transmit during multiple access (MAC) phase, but does not have downlink data to receive during broadcast (BC) phase. This non-simultaneous data exchange will reduce TWR to spectrally-inefficient conventional half-duplex relaying. With infrastructure relays, where multiple users communicate through a relay, a new transmission protocol is proposed to recover the spectral loss. The BC phase following the MAC phase of TUE is now used by the relay to transmit downlink data to another user (RUE). RUE will not be able to cancel the back-propagating interference. A structured precoder is designed at the multi-antenna relay to cancel this interference. With multiple-input multiple-output (MIMO) nodes, the proposed precoder also triangulates the compound MAC and BC phase MIMO channels. The channel triangulation reduces the weighted sum-rate optimization to power allocation problem, which is then cast as a geometric program. Simulation results illustrate the effectiveness of the proposed protocol over conventional solutions.Comment: 30 pages, 7 figures, submitted to IEEE Transactions on Wireless Communication

Flow Decomposition for Multi-User Channels - Part I

A framework based on the idea of flow decomposition is proposed to characterize the decode-forward region for general multi-source, multi-relay, all-cast channels with independent input distributions. The region is difficult to characterize directly when deadlocks occur between two relay nodes, in which both relays benefit by decoding after each other. Rate-vectors in the decode-forward region depend ambiguously on the outcomes of all deadlocks in the channel. The region is characterized indirectly in two phases. The first phase assumes relays can operate non-causally. It is shown that every rate-vector in the decode-forward region corresponds to a set of flow decompositions, which describe the messages decoded at each node with respect to the messages forwarded by all the other nodes. The second phase imposes causal restrictions on the relays. Given an arbitrary set of (possibly non-causal) flow decompositions, necessary and sufficient conditions are derived for the existence of an equivalent set of causal flow decompositions that achieves the same rate-vector region

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Energy Efficient, Cooperative Communication in Low-Power Wireless Networks

The increased interest in massive deployment of wireless sensors and network densification requires more innovation in low-latency communication across multi-hop networks. Moreover, the resource constrained nature of sensor nodes calls for more energy efficient transmission protocols, in order to increase the battery life of said devices. Therefore, it is important to investigate possible technologies that would aid in improving energy efficiency and decreasing latency in wireless sensor networks (WSN) while focusing on application specific requirements. To this end, and based on state of the art Glossy, a low-power WSN flooding protocol, this dissertation introduces two energy efficient, cooperative transmission schemes for low-power communication in WSNs, with the aim of achieving performance gains in energy efficiency, latency and power consumption. These approaches apply several cooperative transmission technologies such as physical layer network coding and transmit beamforming. Moreover, mathematical tools such as convex optimization and game theory are used in order to analytically construct the proposed schemes. Then, system level simulations are performed, where the proposed schemes are evaluated based on different criteria. First, in order to improve over all latency in the network as well as energy efficiency, MF-Glossy is proposed; a communication scheme that enables the simultaneous flooding of different packets from multiple sources to all nodes in the network. Using a communication-theoretic analysis, upper bounds on the performance of Glossy and MF-Glossy are determined. Further, simulation results show that MF-Glossy has the potential to achieve several-fold improvements in goodput and latency across a wide spectrum of network configurations at lower energy costs and comparable packet reception rates. Hardware implementation challenges are discussed as a step towards harnessing the potential of MF-Glossy in real networks, while focusing on key challenges and possible solutions. Second, under the assumption of available channel state information (CSI) at all nodes, centralized and distributed beamforming and power control algorithms are proposed and their performance is evaluated. They are compared in terms of energy efficiency to standard Glossy. Numerical simulations demonstrate that a centralized power control scheme can achieve several-fold improvements in energy efficiency over Glossy across a wide spectrum of network configurations at comparable packet reception rates. Furthermore, the more realistic scenario where CSI is not available at transmitting nodes is considered. To battle CSI unavailability, cooperation is introduced on two stages. First, cooperation between receiving and transmitting nodes is proposed for the process of CSI acquisition, where the receivers provide the transmitters with quantized (e.g. imperfect) CSI. Then, cooperation within transmitting nodes is proposed for the process of multi-cast transmit beamforming. In addition to an analytical formulation of the robust multi-cast beamforming problem with imperfect CSI, its performance is evaluated, in terms of energy efficiency, through numerical simulations. It is shown that the level of cooperation, represented by the number of limited feedback bits from receivers to transmitters, greatly impacts energy efficiency. To this end, the optimization problem of finding the optimal number of feedback bits B is formulated, as a programming problem, under QoS constraints of 5% maximum outage. Numerical simulations show that there exists an optimal number of feedback bits that maximizes energy efficiency. Finally, the effect of choosing cooperating transmitters on energy efficiency is studied, where it is shown that an optimum group of cooperating transmit nodes, also known as a transmit coalition, can be formed in order to maximize energy efficiency. The investigated techniques including optimum feedback bits and transmit coalition formation can achieve a 100% increase in energy efficiency when compared to state of the art Glossy under same operation requirements in very dense networks. In summary, the two main contributions in this dissertation provide insights on the possible performance gains that can be achieved when cooperative technologies are used in low-power wireless networks