Elif Uysal-Biyikoglu

Energy-efficient packet transmission over a wireless link

The paper considers the problem of minimizing the energy used to transmit packets over a wireless link via lazy schedules that judiciously vary packet transmission times. The problem is motivated by the following observation. With many channel coding schemes, the energy required to transmit a packet can be significantly reduced by lowering transmission power and code rate, and therefore transmitting the packet over a longer period of time. However, information is often time-critical or delay-sensitive and transmission times cannot be made arbitrarily long. We therefore consider packet transmission schedules that minimize energy subject to a deadline or a delay constraint. Specifically, we obtain an optimal offline schedule for a node operating under a deadline constraint. An inspection of the form of this schedule naturally leads us to an online schedule which is shown, through simulations, to perform closely to the optimal offline schedule. Taking the deadline to infinity, we provide an exact probabilistic analysis of our offline scheduling algorithm. The results of this analysis enable us to devise a lazy online algorithm that varies transmission times according to backlog. We show that this lazy schedule is significantly more energy-efficient compared to a deterministic (fixed transmission time) schedule that guarantees queue stability for the same range of arrival rates.

Energy-efficient scheduling of packet transmissions over wireless networks

The paper develops algorithms for minimizing the energy required to transmit packets in a wireless environment. It is motivated by the following observation: In many channel coding schemes it is possible to significantly lower the transmission energy by transmitting packets over a long period of time. Based on this observation, we show that for a variety of scenarios the offline energy-efficient transmission scheduling problem reduces to a convex optimization problem. Unlike for the special case of a single transmitter-receiver pair studied by (see Prabhakar, Uysal-Biyikoglu and El Gamal. Proc. IEEE Infocom 2001), the problem does not, in general, admit a closed-form solution when there are multiple users. By exploiting the special structure of the problem, however, we are able to devise energy-efficient transmission schedules. For the downlink channel, with a single transmitter and multiple receivers, we devise an iterative algorithm, called MoveRight, that yields the optimal offline schedule. The MoveRight algorithm also optimally solves the downlink problem with additional constraints imposed by packet deadlines and finite transmit buffers. For the uplink (or multiaccess) problem MoveRight optimally determines the offline time-sharing schedule. A very efficient online algorithm, called MoveRightExpress, that uses a surprisingly small look-ahead buffer is proposed and is shown to perform competitively with the optimal offline schedule in terms of energy efficiency and delay.

Optimal Packet Scheduling on an Energy Harvesting Broadcast Link

The minimization of transmission completion time for a given number of bits per user in an energy harvesting communication system, where energy harvesting instants are known in an offline manner is considered. An achievable rate region with structural properties satisfied by the 2-user AWGN Broadcast Channel capacity region is assumed. It is shown that even though all data are available at the beginning, a non-negative amount of energy from each energy harvest is deferred for later use such that the transmit power starts at its lowest value and rises as time progresses. The optimal scheduler ends the transmission to both users at the same time. Exploiting the special structure in the problem, the iterative offline algorithm, FlowRight, from earlier literature, is adapted and proved to solve this problem. The solution has polynomial complexity in the number of harvests used, and is observed to converge quickly on numerical examples.

On adaptive transmission for energy efficiency in wireless data networks

This paper investigates the problem of energy-efficient transmission of data packets in a wireless network by jointly adapting to backlog and channel condition. Specifically, we consider minimum-energy scheduling problems over multiple-access channels, broadcast channels, and channels with fading, when packets of all users need to be transmitted before a deadline T. Earlier work has considered a similar setup and demonstrated significant transmission energy saving by adapting to backlog for channels that are time invariant and when transmission is restricted to time-division. For concreteness, throughout the paper, rates and powers corresponding to optimal coding over discrete-time additive white Gaussian noise (AWGN) channels are assumed. The results, however, hold for more general channels and coding schemes where the total transmitted power is convex in the transmission rates. The offline scheduling problems for all the channels considered are shown to reduce to convex optimization problems with linear constraints. An iterative algorithm, referred to as FlowRight, that finds optimal offline schedules is presented. A heuristic online algorithm that we call look-ahead water-filling, which jointly adapts to both channel fading state and backlog is described. By the use of a small buffer which introduces an almost fixed delay, this algorithm achieves a considerable reduction in energy relative to water filling solely on channel states.

MIMO Broadcast Scheduling with Quantized Channel State Information

We develop and analyze a simple, low-complexity system architecture for scheduling over a Gaussian multiple-input multiple-output (MIMO) broadcast channel with infinite message backlogs. In the system of interest, there is a transmitter with m antennas, and n receiving users, where n Gt m. We show that the proposed architecture is strongly asymptotically optimal with respect to average throughput. We further characterize the feedback requirements of the architecture, and highlight various tradeoffs available to the system designer

Review: Energy efficient wireless unicast routing alternatives for machine-to-machine networks

Machine-to-machine (M2M) communications is a new and rapidly developing technology for large-scale networking of devices without dependence on human interaction. Energy efficiency is one of the important design objectives for machine-to-machine network architectures that often contain multi-hop wireless subnetworks. Constructing energy-efficient routes for sending data through such networks is important not only for the longevity of the nodes which typically depend on battery energy, but also for achieving an environmentally friendly system design overall, which will be imperative as M2M networks scale in number of nodes as projected. The objective of this survey is to provide a comprehensive look into shortest-path based energy-efficient routing alternatives to provide a reference for system designers as well as researchers. We start by describing M2M and its application areas, as well as its challenges. Next, a detailed account of energy-efficient unicast routing alternatives, with a particular focus on those based on additive link cost is given. Following a novel comprehensive classification of shortest-path-based energy-efficient routing algorithms designed for wireless ad hoc and sensor networks, we end by comparisons and discussions of the use of different cost metrics.

Age of information under energy replenishment constraints

We consider managing the freshness of status updates sent from a source (such as a sensor) to a monitoring node. The time-varying availability of energy at the sender limits the rate of update packet transmissions. At any time, the age of information is defined as the amount of time since the most recent update was successfully received. An offline solution that minimizes not only the time average age, but also the peak age for an arbitrary energy replenishment profile is derived. The related decision problem under stochastic energy arrivals at the sender is studied through a discrete time dynamic programming formulation, and the structure of the optimal policy that minimizes the expected age is shown. It is found that tracking the expected value of the current age (which is a linear operation), together with the knowledge of the current energy level at the sender side is sufficient for generating an optimal threshold policy. An effective online heuristic, Balance Updating (BU), that achieves performance close to an omniscient (offline) policy is proposed. Simulations of the policies indicate that they can significantly improve the age over greedy approaches. An extension of the formulation to stochastically formed updates is considered.

Energy harvesting communication networks: Optimization and demonstration (the E-CROPS project)

We describe the new European project E-CROPS which was ranked first in the 2012 CHIST-ERA competition. This project has begun its work in February 2013 to develop a system-wide approach to using energy harvesting and smart energy management technologies in communication and mobile devices. The project will examine energy-dependent fundamental limits of communications, together with the timely harvesting, storage and delivery of energy to the computing and communication units of these devices, to achieve an optimal balance between the quality of service, performance, and efficient usage of energy. E-CROPS will combine theoretical modelling and performance analysis with experimental demonstrations bringing together four collaborating teams from France (EURECOM), Spain (CTTC), Turkey (METU) and the UK (Imperial College London).

Finding NEMO: near mutually orthogonal sets and applications to MIMO broadcast scheduling

We define a near-orthogonal set of channel vectors as one that meets certain SIR and SNR guarantees. The probability of finding a near-orthogonal set in a pool of n users is characterized. We identify a phase transition phenomenon in channel geometry whereby this probability transitions from 0 to 1 as k, the number of users that have been examined, increases. It is shown that after this transition the probability of failing to find such a set behaves like /spl theta/(k/sup -m/). The rate at which SNR and SIR can be scaled while we remain above this threshold is also characterized. The existence results we provide are not specific to the MIMO scheduling problem, but apply to the more general setting of finding a near-orthogonal set in a random collection of isotropic vectors. The proofs make use of new tight bounds we develop to bound the surface content of spherical caps in arbitrary dimensions. Broader implications of these results are discussed. Specifically, in the case of zero-forcing the best sum rate achievable increases at a rate on the order of log log n.

Optimal offline broadcast scheduling with an energy harvesting transmitter

We consider an energy harvesting transmitter broadcasting individual data to two receivers. Data packets intended for each user are assumed to arrive at arbitrary but known instants. The goal is to minimize the total transmission time of the packets arriving within a certain time window, using the energy harvested during this time. Energy harvests are also modelled to occur at known discrete instants. An achievable rate region with structural properties satisfied by the two-user additive white Gaussian noise broadcast channel capacity region is assumed. Structural properties of power and rate allocations are established, as well as the uniqueness of the optimal policy. An iterative algorithm, DuOpt, is devised for efficient solution of this offline problem. DuOpt is compared with the sequential unconstrained minimization (SUMT) solution technique on randomly generated problem instances and is observed to solve the problem two orders of magnitude faster on average than SUMT.