Robust Smart-Grid-Powered Cooperative Multipoint Systems

Abstract

A framework is introduced to integrate renewable energy sources (RES) and dynamic pricing capabilities of the smart grid into beamforming designs for coordinated multi-point (CoMP) downlink communication systems. To this end, novel models are put forth to account for harvesting, storage of nondispatchable RES, time-varying energy pricing, as well as stochastic wireless channels. Building on these models, robust energy management and transmit-beamforming designs are developed to minimize the worst-case energy cost subject to the worstcase user QoS guarantees for the CoMP downlink. Leveraging pertinent tools, this task is formulated as a convex problem. A Lagrange dual based subgradient iteration is then employed to find the desired optimal energy-management strategy and transmit-beamforming vectors. Numerical results are provided to demonstrate the merits of the proposed robust designs.

Modeling and Analysis of Energy Harvesting and Smart Grid-Powered Wireless Communication Networks: A Contemporary Survey

“…Due to an unbalanced supply of RES and energy requirements across geographically dispersed BSs, and a considerable price gap of the BSs purchasing (or selling) electricity from (or towards) the smart energy grid, it is cost-effective for these BSs to collectively plan their transactional dealings with the smart energy grid, as well as electricity usage for CoMP-enabled communications. A framework is developed in [114] to capture finite storage, bidirectional electricity trading and dynamic pricing of the smart grid into CoMP downlink communication systems with imperfect channel state information (CSI) at the transmitter. The system model is pictorially illustrated in Fig.…”

“…The authors of [114] develop the worst-case energy scheduling and transmit beamforming schemes to minimize the system-wide transaction expenditure, while guaranteeing user QoS in a CoMP-enabled downlink network. Let P t b,i stand for the power transferred into, or taken out of, the batteries at slot t for BS i.…”

Optimal resource allocation for smart-grid powered MIMO broadcast channels

“…Regarding this issue, we resort to the proximal bundle method to efficiently obtain { ( )} =1 ; see details in [3].…”

“…However, the current power network infrastructure is migrating from the aging grid to a "smart" one. The future smart grid has many appealing features and advanced capabilities including e.g., renewable energy sources (RES), two-way energy trading, dynamic pricing based demand-side management, as well as decentralized control [3]- [5].…”

“…Adopting simplified system models with a limited smart-grid capability, a few recent works dealt with the energy-efficient resource allocation for smart-grid powered coordinated downlink transmissions; see e.g., [8]. Building on practical smart-grid models This for a green coordinated multi-point (CoMP) system, our recent work [3] developed robust energy management and transmitbeamforming designs that minimize the worst-case energy transaction cost with a guaranteed quality-of-service (QoS). However, none of these existing works considered the impact of advanced smart-grid capabilities on the achievable rate limits of the BCs.…”