Alireza Seyedi

Energy Efficient Transmission Strategies for Body Sensor Networks with Energy Harvesting

This paper addresses the problem of developing energy efficient transmission strategies for Body Sensor Networks (BSNs) with energy harvesting. It is assumed that multiple transmission modes that allow a tradeoff between the energy consumption and packet error probability are available to the sensor nodes. Taking into account the energy harvesting capabilities of the nodes, decision policies are developed to determine the transmission mode to use at a given instant of time in order to maximize the quality of coverage. The problem is formulated as a Markov Decision Process (MDP) and the performance of the transmission policy thus derived is compared with that of energy balancing as well as aggressive policies. An upper bound on the performance of arbitrary policies, and lower bounds specific to energy balancing and aggressive policies are derived.

Optimizing physical-layer parameters for wireless sensor networks

As wireless sensor networks utilize battery-operated nodes, energy efficiency is of paramount importance at all levels of system design. In order to save energy in the transfer of data from the sensor nodes to one or more sinks, the data may be routed through other nodes rather than transmitting it directly to the sink(s). In this article, we investigate the problem of energy-efficient transmission of data over a noisy channel, focusing on the setting of physical-layer parameters. We derive a metric called the energy per successfully received bit, which specifies the expected energy required to transmit a bit successfully over a particular distance given a channel noise model. By minimizing this metric, we can find, for different modulation schemes, the energy-optimal relay distance and the optimal transmit energy as a function of channel noise level and path loss exponent. These results enable network designers to select the hop distance, transmit power, and/or modulation scheme that maximize network lifetime.

Energy efficient transmission strategies for Body Sensor Networks with energy harvesting

This paper addresses the problem of developing energy efficient transmission strategies for Body Sensor Networks (BSNs) with energy harvesting. It is assumed that multiple transmission modes that allow a tradeoff between the energy consumption and packet error probability are available to the sensor nodes. Taking into account the energy harvesting capabilities of the nodes, decision policies are developed to determine the transmission mode to use at a given instant of time in order to maximize the quality of coverage. The problem is formulated as a Markov Decision Process (MDP) and the performance of the transmission policy thus derived is compared with that of energy balancing as well as aggressive policies. An upper bound on the performance of arbitrary policies, and lower bounds specific to energy balancing and aggressive policies are derived.

Modeling and analysis of energy harvesting nodes in wireless sensor networks

A Markov based unified model for energy harvesting nodes in wireless sensor networks is proposed. Using the presented model, the probability of event loss due to energy run out as well as an analytical vulnerability metric, namely average time to energy run-out, are derived. The results provide insight into the performance of energy harvesting nodes in wireless sensor networks as well as design requirements for such nodes. The proposed vulnerability metric can be used in the various harvesting aware techniques at different protocol layers.

An Analytical Approach to the Design of Energy Harvesting Wireless Sensor Nodes

Energy harvesting is one of the promising solutions to the problem of limited battery capacity in many wireless devices. This paper addresses the problem of system design of energy harvesting capable wireless devices in terms of the required sizes for energy and data buffers, as well as the size of the harvester, for given delay and loss requirements. We analyze the performance of an energy harvesting node, considering a stochastic model that takes into account energy harvesting and event arrival processes. We derive closed-form expressions for the probability of event loss and the average queueing delay. Our event-driven continuous time simulations validate our analytical results. Employing these results, we provide a near-optimal approach to the design of the system in terms of sizing the energy harvesting device, the energy storage, and the event queue capacity.

Minimization of transceiver energy consumption in wireless sensor networks with AWGN channels

In this paper, we determine how to minimize energy consumption per information bit in a single link, with the consideration of packet retransmission and overhead. This is achieved by deriving expressions for the optimum target bit error probability and packet length at different transmission distances. Furthermore, the energy consumptions of different modulation schemes are compared over an additive white Gaussian noise (AWGN) channel. Finally, it is shown that the optimum target bit error probability and packet length converge to a constant value for long distances. Numerical results show that at short distances, it is optimum to use bandwidth efficient modulation with large packets and low target BER, and at long distances, it is optimum to use energy efficient modulation with short packets and high target BER.

Stabilization of Networked Control Systems With Sparse Observer-Controller Networks

In this technical note we provide a set of stability conditions for linear time-invariant networked control systems with arbitrary topology, using a Lyapunov direct approach. We then use these stability conditions to provide a novel low-complexity algorithm for the design of a sparse observer-based control network. We employ distributed observers by employing the output of other nodes to improve the stability of each observer dynamics. To avoid unbounded growth of controller and observer gains, we impose bounds on their norms. The effects of relaxation of these bounds is discussed when trying to find the complete decentralization conditions.

Modeling and analysis of energy harvesting nodes in body sensor networks

A Markov based unified model for an energy harvesting node in a body sensor network is presented. Using the presented model, the probability of event loss due to energy run out is calculated. The results provide insight into the performance of energy harvesting nodes in a body sensor network as well as design requirements for such devices.

Synchronization Probability in Large Complex Networks

In a generalized framework, where multistate and interstate linkages are allowed, the synchronization of oscillators in random networks is investigated. A sufficient condition for the stability of synchronization is derived, which explicitly relates the network structure and the local and coupling dynamics to synchronization stability. This condition is then translated into a lower bound on the probability of stability of synchrony for large Erdös-Rényi and Newman-Watts small-world networks.

Link Energy Minimization in IR-UWB Based Wireless Networks

Impulse Radio Ultra WideBand (IR-UWB) communication has proven to be an important technique for supporting high-rate, short-range, and low-power communication. In this paper, using detailed models of typical IR-UWB transmitter and receiver structures, we model the energy consumption per information bit in a single link of an IR-UWB system, considering packet overhead, retransmissions, and a Nakagami-m fading channel. Using this model, we minimize the energy consumption per information bit by finding the optimum packet length and the optimum number of RAKE fingers at the receiver for different transmission distances, using Differential Phase-shift keying (DBPSK), Differential Pulse-position Modulation (DPPM) and On-off Keying (OOK), with coherent and non-coherent detection. Symbol repetition schemes with hard decision (HD) combining and soft decision (SD) combining are also compared in this paper. Our results show that at very short distances, it is optimum to use large packets, OOK with non-coherent detection, and HD combining, while at longer distances, it is optimum to use small packets, DBPSK with coherent detection, and SD combining. The optimum number of RAKE fingers are also found for given transmission schemes.