[Paper Review] Optimal Pricing and Load Sharing for Energy Saving in Communications Cooperation

Yinghao Guo, Lingjie Duan+1 more|arXiv (Cornell University)|Sep 30, 2014

Advanced MIMO Systems Optimization21 references19 citations

TL;DR

This paper proposes a pricing-based cooperative communication framework to enable energy-efficient uplink transmission in cellular networks, where energy-constrained mobile terminals (MTs) pay nearby high-battery MTs to relay their data. By formulating an optimization problem for pricing and load sharing, the scheme reduces MT energy consumption and battery outages while increasing average battery levels, with efficient algorithms for both splittable and non-splittable data.

ABSTRACT

In this paper, we propose a pricing mechanism for the uplink communication cooperation to save the energy of mobile terminals (MTs) in wireless cellular network. Under the uncertainties of the other MTs' channel and battery conditions, a source MT in low battery level or bad channel condition is allowed to select and pay another MT in proximity to help forward its data package to the base station (BS). We formulate the source MT's pricing and load sharing problem as an optimization problem to minimize its expected energy cost. When the source MT cannot split its data package for a certain multimedia application, we motivate the selected relay MT to forward the whole data package by obtaining the optimal pricing through a dichotomous search algorithm. When the source MT can split the data package, we jointly optimize the pricing and load sharing with the relay MT and propose an alternating optimization algorithm that achieves near-optimal solution. Extensive numerical results are provided to show that our proposed pricing mechanism can significantly decrease the source MT's expected energy cost, and load sharing is more cost-efficient when the size of the data package is large and the average number of helping MTs is small.

Motivation & Objective

• Address the lack of incentives for mobile terminals (MTs) to cooperate in energy-saving cooperative communications due to self-interest and battery heterogeneity.
• Design a practical pricing mechanism that enables MTs with low battery or poor channel conditions to pay nearby high-battery MTs for uplink relaying.
• Optimize the source MT’s pricing and data load sharing strategy to minimize energy consumption while ensuring reliable transmission.
• Develop efficient algorithms for both splittable and non-splittable data cases under partial cooperation with incomplete channel and battery information.
• Evaluate the impact of the proposed scheme on reducing communications and battery outages, and improving average battery levels during operation.

Proposed method

• Formulate a relay selection problem under complete information as a benchmark, assuming full knowledge of helping MTs’ channel and battery states.
• Propose a partial cooperation scheme with pricing where the source MT selects and pays a relay based on channel quality and battery level.
• Model the source MT’s energy cost as a function of pricing, data load, and relay efficiency, incorporating outage probability and energy consumption.
• Use dichotomous search and alternative optimization to solve the non-convex optimization problem for splittable and non-splittable data, respectively.
• Derive analytical expressions for the optimal data load sharing and pricing using second-order derivative analysis and stationary point conditions.
• Prove marginal convexity of the objective function with respect to pricing and data load, enabling convergence of the proposed algorithms.

Experimental results

Research questions

• RQ1 How can a pricing mechanism incentivize energy-constrained MTs to cooperate in uplink transmission without relying on altruism?
• RQ2 What is the optimal pricing and load sharing strategy for a source MT to minimize energy consumption when relaying data via a nearby MT?
• RQ3 How does the performance of the proposed scheme compare to non-cooperative or full-cooperation models in terms of energy savings and battery outage?
• RQ4 What are the optimal data load splitting and pricing policies under splittable and non-splittable data constraints?
• RQ5 How does the scheme affect the average battery level and reliability (outage probability) of MTs during operation?

Key findings

• The proposed pricing and load sharing mechanism significantly reduces both communications and battery outages for mobile terminals.
• The scheme increases the average battery level of MTs during operation, extending their operational lifetime.
• For the splittable data case, the optimal data load is derived as $ \hat{D}_{i}^{(R)} = \frac{1}{2}\left(D_{i} + \log_{2}\frac{\theta_{i}}{\theta_{j}}\right) $, depending on the relative energy efficiency of the source and relay.
• The algorithm converges efficiently using dichotomous search and alternative optimization, ensuring practical deployment.
• The objective function is marginally convex with respect to pricing and data load, enabling reliable optimization under uncertainty.
• Numerical results confirm that the scheme outperforms non-cooperative and full-cooperation benchmarks in energy efficiency and reliability.