Showing papers by "Mats Viberg published in 2016"
10 Jul 2016
TL;DR: Performance bounds on the achievable distortion under a slotted block transmission scheme, where at each transmission time slot, the data and the energy buffer is completely emptied, are provided and suggest performance improvements with increasing buffer size for signals with relatively higher degree of freedom.
Abstract: Remote estimation with an energy harvesting sensor with a limited data buffer is considered. The sensor node observes an unknown correlated circularly wide-sense stationary (c.w.s.s.) Gaussian field and communicates its observations to a remote fusion center using the energy it harvested. The fusion center employs minimum mean-square error (MMSE) estimation to reconstruct the unknown field. The distortion minimization problem under the online scheme, where the sensor has only access to the statistical information for the future energy packets is considered. We provide performance bounds on the achievable distortion under a slotted block transmission scheme, where at each transmission time slot, the data and the energy buffer is completely emptied. Our bounds provide insight to the trade-off between the buffer sizes and the achievable distortion. These trade-offs illustrate the insensitivity of the performance to the buffer size for signals with low degree of freedom and suggest performance improvements with increasing buffer size for signals with relatively higher degree of freedom.
7 citations
TL;DR: The proposed method is to decompose the array response as a product of a mutual coupling matrix, an ideal array response vector (dependent on the geometry of antenna array) and a DOA-dependent correction vector, which will be a smoother function of DOA as compared to direct interpolation.
7 citations
Posted Content•
TL;DR: In this article, the authors considered the problem of minimizing the mean-square error at the fusion center of a time-correlated signal using an EH sensor and provided the optimal power allocation strategies for a number of illustrative scenarios.
Abstract: We consider the remote estimation of a time-correlated signal using an energy harvesting (EH) sensor. The sensor observes the unknown signal and communicates its observations to a remote fusion center using an amplify-and-forward strategy. We consider the design of optimal power allocation strategies in order to minimize the mean-square error at the fusion center. Contrary to the traditional approaches, the degree of correlation between the signal values constitutes an important aspect of our formulation. We provide the optimal power allocation strategies for a number of illustrative scenarios. We show that the most majorized power allocation strategy, i.e. the power allocation as balanced as possible, is optimal for the cases of circularly wide-sense stationary (c.w.s.s.) signals with a static correlation coefficient, and sampled low-pass c.w.s.s. signals for a static channel. We show that the optimal strategy can be characterized as a water-filling type solution for sampled low-pass c.w.s.s. signals for a fading channel. Motivated by the high-complexity of the numerical solution of the optimization problem, we propose low-complexity policies for the general scenario. Numerical evaluations illustrate the close performance of these low-complexity policies to that of the optimal policies, and demonstrate the effect of the EH constraints and the degree of freedom of the signal.
5 citations
01 Aug 2016
TL;DR: The remote estimation of a time-correlated field using an energy harvesting (EH) sensor and the design of optimal transmission strategies in order to minimize the mean-square error at the fusion center are considered.
Abstract: We consider the remote estimation of a time-correlated field using an energy harvesting (EH) sensor. The sensor observes the unknown field and communicates its observations to a remote fusion center using an amplify-forward strategy. We consider the design of optimal transmission strategies in order to minimize the mean-square error (MSE) at the fusion center. Contrary to traditional approaches, the degree of correlation between the field values constitutes an important aspect of our formulation. We provide the optimal power allocation strategies for a number of illustrative scenarios, including the circularly wide-sense stationary (c.w.s.s.) signals with static correlation coefficient and the sampled low-pass c.w.s.s. signals. Based on these results, we propose low-complexity policies for the general case. Numerical evaluations illustrate the performance of the optimal and the low-complexity policies.
4 citations
01 Sep 2016
TL;DR: This work adopts an experimentally validated additive noise model in which the level of the noise at an antenna is proportional to the signal power at that antenna, which constitutes a non-convex formulation for the single antenna information user case.
Abstract: We investigate the performance of a communication system with simultaneous wireless information and power transfer capabilities under non-ideal transmitter hardware. We adopt an experimentally validated additive noise model in which the level of the noise at an antenna is proportional to the signal power at that antenna. We consider the linear precoder design problem and focus on the problem of minimizing the mean-square error under energy harvesting constraints. This set-up, in general, constitutes a non-convex formulation. For the single antenna information user case, we provide a tight convex relaxation, i.e. a convex formulation from which an optimal solution for the original problem can be constructed. For the general case, we propose a block coordinate descent technique to solve the resulting non-convex problem. Our numerical results illustrate the effect of hardware impairments on the system.
1 citations
Posted Content•
TL;DR: Borders provide insights to the trade-offs between the buffer sizes, the statistical properties of the energy harvesting process and the achievable distortion and suggest performance improvements with increasing buffer size for signals with relatively higher degree of freedom.
Abstract: Remote estimation with an energy harvesting sensor with a limited data and energy buffer is considered. The sensor node observes an unknown Gaussian field and communicates its observations to a remote fusion center using the energy it harvested. The fusion center employs minimum mean-square error (MMSE) estimation to reconstruct the unknown field. The distortion minimization problem under the online scheme, where the sensor has access to only the statistical information for the future energy packets is considered. We provide performance bounds on the achievable distortion under a slotted block transmission scheme, where at each transmission time slot, the data and the energy buffer are completely emptied. Our bounds provide insights to the trade-offs between the buffer sizes, the statistical properties of the energy harvesting process and the achievable distortion. In particular, these trade-offs illustrate the insensitivity of the performance to the buffer sizes for signals with low degree of freedom and suggest performance improvements with increasing buffer size for signals with relatively higher degree of freedom. Depending only on the mean, variance and finite support of the energy arrival process, these results provide practical insights for the battery and buffer sizes for deployment in future energy harvesting wireless sensing systems.