Communicating Using an Energy Harvesting Transmitter: Optimum Policies Under Energy Storage Losses

In this paper, short-term throughput optimal power allocation policies are derived for an energy harvesting transmitter with energy storage losses. In particular, the energy harvesting transmitter is equipped with a battery that loses a fraction of its stored energy. Both single user, i.e. one transmitter-one receiver, and the broadcast channel, i.e., one transmitter-multiple receiver settings are considered, initially with an infinite capacity battery. It is shown that the optimal policies for these models are threshold policies. Specifically, storing energy when harvested power is above an upper threshold, retrieving energy when harvested power is below a lower threshold, and transmitting with the harvested energy in between is shown to maximize the weighted sum-rate. It is observed that the two thresholds are related through the storage efficiency of the battery, and are nondecreasing during the transmission. The results are then extended to the case with finite battery capacity, where it is shown that a similar double-threshold structure arises but the thresholds are no longer monotonic. A dynamic program that yields an optimal online power allocation is derived, and is shown to have a similar double-threshold structure. A simpler online policy is proposed and observed to perform close to the optimal policy.Comment: Submitted to IEEE Transactions on Wireless Communications, August 201

Smart Meter Privacy with an Energy Harvesting Device and Instantaneous Power Constraints

A smart meter (SM) periodically measures end-user electricity consumption and reports it to a utility provider (UP). Despite the advantages of SMs, their use leads to serious concerns about consumer privacy. In this paper, SM privacy is studied by considering the presence of an energy harvesting device (EHD) as a means of masking the user's input load. The user can satisfy part or all of his/her energy needs from the EHD, and hence, less information can be leaked to the UP via the SM. The EHD is typically equipped with a rechargeable energy storage device, i.e., a battery, whose instantaneous energy content limits the user's capability in covering his/her energy usage. Privacy is measured by the information leaked about the user's real energy consumption when the UP observes the energy requested from the grid, which the SM reads and reports to the UP. The minimum information leakage rate is characterized as a computable information theoretic single-letter expression when the EHD battery capacity is either infinite or zero. Numerical results are presented for a discrete binary input load to illustrate the potential privacy gains from the existence of a storage device.Comment: To be published in IEEE ICC201

On Resource Allocation in Fading Multiple Access Channels - An Efficient Approximate Projection Approach

We consider the problem of rate and power allocation in a multiple-access channel. Our objective is to obtain rate and power allocation policies that maximize a general concave utility function of average transmission rates on the information theoretic capacity region of the multiple-access channel. Our policies does not require queue-length information. We consider several different scenarios. First, we address the utility maximization problem in a nonfading channel to obtain the optimal operating rates, and present an iterative gradient projection algorithm that uses approximate projection. By exploiting the polymatroid structure of the capacity region, we show that the approximate projection can be implemented in time polynomial in the number of users. Second, we consider resource allocation in a fading channel. Optimal rate and power allocation policies are presented for the case that power control is possible and channel statistics are available. For the case that transmission power is fixed and channel statistics are unknown, we propose a greedy rate allocation policy and provide bounds on the performance difference of this policy and the optimal policy in terms of channel variations and structure of the utility function. We present numerical results that demonstrate superior convergence rate performance for the greedy policy compared to queue-length based policies. In order to reduce the computational complexity of the greedy policy, we present approximate rate allocation policies which track the greedy policy within a certain neighborhood that is characterized in terms of the speed of fading.Comment: 32 pages, Submitted to IEEE Trans. on Information Theor