Price-Based Bandwidth Allocation for Backscatter Communication With Bandwidth Constraints

Liu, Dong; Liang, Ying-Chang

doi:10.1109/twc.2019.2934101

Cited by 34 publications

(10 citation statements)

References 38 publications

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“…In [16] a cooperative distributed interference pricing algorithm is proposed for power control in heterogeneous wireless networks. In [17] a Stackelberg game is formulated to study the price-based bandwidth allocation in multi-user Bluetooth low energy (BLE)-backscatter communication. In [18] a hierarchical auction-based mechanism is designed to reduce both global communication and unnecessary repeated computation in ad hoc networks.…”

Section: Main Results a Game Modeling Based On Network Pricingmentioning

confidence: 99%

Dynamic Bandwidth Scheduling of Software Defined Networked Collaborative Control System

2020

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From the perspective of collaborative design of control and scheduling, a software-defined networked collaborative control system (SD-NCCS) is established. On this basis, the system performance of SD-NCCS is analyzed and the average sensitivities of reference are used in utility function to evaluate the effects of network-induced delays. Moreover, the network pricing mechanism and game theory are introduced and a dynamic bandwidth resource allocation model of the overall control system for optimal performance is obtained. Thus, the problem of the network resource allocation of the SD-NCCS has been converted to be the problem of solving the Nash equilibrium point under the non-cooperative game model. Furthermore, the Nash equilibrium solution under this frame is obtained using the estimation distributed algorithm (EDA). Finally, a simple example is included to illustrate the performance of our scheme. INDEX TERMS Estimation of distribution algorithm, game theory, network pricing, software-defined network.

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Section: Main Results a Game Modeling Based On Network Pricingmentioning

confidence: 99%

Dynamic Bandwidth Scheduling of Software Defined Networked Collaborative Control System

2020

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“…where B is the system bandwidth, σ 2 denotes the thermal noise power spectral density, ε i ∈ (0, 1) is the scattering efficiency of the transmit antenna at the i-th IoT device [22], [30] and ξ (0 ≤ ξ ≤ 1) reflects the performance gap between the BackCom and the active transmission [14], [25], [26]. Correspondingly, the harvested energy at the i-th IoT device in this sub-phase can be computed as…”

Section: System Modelmentioning

confidence: 99%

“…Accordingly, the transmitter in BackComs bypasses the need of energy-consuming active components for generating carrier signals and BackCom is recognized as an ultra low-power communication technology. Due to different operation principles, WPCN and Back-Com have different tradeoffs between the achievable rate and the energy consumption, i.e., BackCom achieves much less rate but consumes much less energy compared with WPCN [4], [14].…”

Section: Introductionmentioning

confidence: 99%

Max-Min Throughput in Hybrid of Wireless Powered NOMA and Backscatter Communications

Zhou

2020

IEEE Access

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“…For BackCom, we assume that successive interference cancellation (SIC) is performed at the MEC server to remove the interference caused by the PB-to-MEC server link 3 . Then, based on [11], the achievable offloading throughput of the kth EU via BackCom in the first phase can be expressed as…”

Section: System Modelmentioning

confidence: 99%

“…, where ξ is the performance gap between the BackCom and the AT [11], [12], B, P t and σ 2 denote the channel bandwidth, the PB's transmit power, and the thermal noise power spectral density, respectively.…”

Section: System Modelmentioning

confidence: 99%

Computation Bits Maximization in a Backscatter Assisted Wirelessly Powered MEC Network

Shi,

Ye,

Chu

et al. 2020

Preprint

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In this paper, we introduce a backscatter assisted wirelessly powered mobile edge computing (MEC) network, where each edge user (EU) can offload task bits to the MEC server via hybrid harvest-then-transmit (HTT) and backscatter communications. In particular, considering a practical non-linear energy harvesting (EH) model and a partial offloading scheme at each EU, we propose a scheme to maximize the weighted sum computation bits of all the EUs by jointly optimizing the backscatter reflection coefficient and time, active transmission power and time, local computing frequency and execution time of each EU. By introducing a series of auxiliary variables and using the properties of the non-linear EH model, we transform the original non-convex problem into a convex one and derive closedform expressions for parts of the optimal solutions. Simulation results demonstrate the advantage of the proposed scheme over benchmark schemes in terms of weighted sum computation bits.

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Price-Based Bandwidth Allocation for Backscatter Communication With Bandwidth Constraints

Cited by 34 publications

References 38 publications

Dynamic Bandwidth Scheduling of Software Defined Networked Collaborative Control System

Dynamic Bandwidth Scheduling of Software Defined Networked Collaborative Control System

Max-Min Throughput in Hybrid of Wireless Powered NOMA and Backscatter Communications

Computation Bits Maximization in a Backscatter Assisted Wirelessly Powered MEC Network

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