3 research outputs found
A Bandit Approach for Mode Selection in Ambient Backscatter-Assisted Wireless-Powered Relaying
Backscattering assisted wireless-powered communication combines
ultralow-power backscatter transmitters with energy harvesting devices. This
paper investigates the transmission mode selection problem of a hybrid relay
that forwards data by switching between the active wireless-powered
transmission and the passive ambient backscattering. It first presents a hybrid
relay system model and derives its end-to-end success probability under
theoretically optimal, but practically unrealistic, conditions. The
transmission mode selection is then formulated as a stochastic two-armed bandit
problem in a varying environment where the distributions of rewards are
nonstationary. The proposed model selection scheme does not assume to have
access to any channel states or network conditions, but merely relies on
learning from past transmission records. Numerical analyses are performed to
validate the proposed bandit-based mode selection approach.Comment: IEEE TV
A Non-Stationary Bandit-Learning Approach to Energy-Efficient Femto-Caching with Rateless-Coded Transmission
The ever-increasing demand for media streaming together with limited backhaul
capacity renders developing efficient file-delivery methods imperative. One
such method is femto-caching, which, despite its great potential, imposes
several challenges such as efficient resource management. We study a resource
allocation problem for joint caching and transmission in small cell networks,
where the system operates in two consecutive phases: (i) cache placement, and
(ii) joint file- and transmit power selection followed by broadcasting. We
define the utility of every small base station in terms of the number of
successful reconstructions per unit of transmission power. We then formulate
the problem as to select a file from the cache together with a transmission
power level for every broadcast round so that the accumulated utility over the
horizon is maximized. The former problem boils down to a stochastic knapsack
problem, and we cast the latter as a multi-armed bandit problem. We develop a
solution to each problem and provide theoretical and numerical evaluations. In
contrast to the state-of-the-art research, the proposed approach is especially
suitable for networks with time-variant statistical properties. Moreover, it is
applicable and operates well even when no initial information about the
statistical characteristics of the random parameters such as file popularity
and channel quality is available
Device-to-Device Communications Underlaying Cellular Networks: To Use Unlicensed Spectrum or Not?
In this paper, we consider device-to-device (D2D) communications as an
underlay to the cellular networks over both licensed and unlicensed spectrum,
where Long Term Evolution (LTE) users utilize the spectrum orthogonally while
D2D users share the spectrum with LTE users. In the system, each LTE and D2D
user can access the licensed or unlicensed band for communications. To maximize
the total throughput of the system, we leverage stochastic geometry to derive
the throughput for each kind of users by modeling the deployment of users as
Poisson point processes (PPPs), and investigate the spectrum access problem for
these users. Since the problem is NP-hard, we propose a sequential quadratic
programming (SQP) based algorithm to obtain the corresponding suboptimal
solutions. Theoretically, we evaluate the system performance by analyzing the
throughput regions. Simulation results validate the accuracy of the geometric
analysis and verify the effectiveness of the proposed algorithm.Comment: 14 pages, 9 figures, Journa