Optimal Packet Scheduling on an Energy Harvesting Broadcast Link (1010.4876v2)

Abstract: 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.

• The paper introduces an optimal scheduling framework that minimizes transmission time by deferring a portion of harvested energy.
• It adapts the FlowRight algorithm to compute unique power-rate pairs for simultaneous data delivery in a multiuser AWGN broadcast setting.
• The proposed method scales polynomially with energy harvest intervals, and numerical evaluations confirm non-decreasing power and rate allocations.

Optimal Packet Scheduling on an Energy Harvesting Broadcast Link

The paper presents a comprehensive paper on minimizing transmission completion time for an energy harvesting communication system operating over an AWGN Broadcast Channel with prior knowledge of energy harvesting instants. This research builds upon previous works that focus on energy-efficient transmission scheduling, expanding the domain to multiuser scenarios with one sender and multiple receivers. The main challenge addressed is optimizing the schedule to minimize the time required to transmit a set number of bits to each user while managing energy harvested at known intervals.

Key Contributions and Methodology

1. Formulation and Structural Properties: The research articulates the problem of minimizing transmission time given pre-known energy harvesting points over a broadcast channel modeled by AWGN. It assumes an achievable rate region with properties consistent with the two-user AWGN channel, including monotonicity and convexity concerning the power and rate pair. The primary observation is that even with all data available at the outset, deferring a non-negative portion of harvested energy is optimal, allowing transmit power to start low and increase over time, culminating in all users receiving data simultaneously.
2. Adaptation of FlowRight Algorithm: Building on earlier literature, the paper adapts the FlowRight algorithm to solve the formulated optimization problem. The adaptation addresses the need for simultaneously determining rates and power allocations since each rate pair corresponds to a unique power level on the boundary of the capacity region. The iterative nature of FlowRight efficiently finds a schedule by improving upon the initial feasible solution using local optimizations on epoch pairs.
3. Complexity and Implementation: The complexity analysis demonstrates that the solution process scales polynomially with the number of energy harvests, making it feasible for practical implementation. The initialization step ensures that the initial schedule is feasible, and each iteration of FlowRight guarantees a strict improvement towards optimal completion time.
4. Numerical Evaluation and Properties of the Solution: The paper presents results showing how powers and rates are allocated following the fundamental properties derived theoretically—specifically, that power and user rates are non-decreasing over time within the optimal schedule. The numerical example further illustrates these findings, demonstrating the algorithm's practical applicability and convergence speed.

Implications and Future Directions

The implications of this work are twofold: theoretically, it enhances our understanding of energy scheduling strategies in communication systems with energy constraints. Practically, it suggests efficient scheduling methodologies for systems where energy availability might be sporadic or limited, such as remote sensors or IoT devices powered by energy harvesting technologies.

The paper lays a foundation for several potential developments in the field:

• Dynamic and Online Scheduling: Exploration of solutions under dynamic or stochastic settings, where energy arrivals and data packets are not pre-known, could introduce more complexity and necessitate real-time adaptive algorithms.
• Multi-Sender Scenarios: Adapting the model to scenarios with multiple senders, which could introduce additional constraints and necessitate cooperative strategies among nodes.
• Application to Time-Varying Channels: Investigating how time-varying channel gains might affect the optimal scheduling and how adaptive algorithms could cater to such variations in an online fashion.

This paper significantly contributes to the domain of energy-efficient scheduling in multiuser environments, providing insights and methodologies that can be extended to various practical applications in next-generation wireless networks.