PhD Student, Indian Institute of Technology Kanpur
Resource allocation algorithms for wireless networks which harvest energy from the environment
"Internet of things (IoT) is the future". IoT is the next generation concept in which billions of everyday objects are connected to the internet without requiring human interaction. Such devices are enabled with sensors to gather relevant information and share it with the intended receiver over the internet. These devices require energy for their sustained operation and frequent battery replacement is not possible in most of the cases. Therefore, energy harvesting techniques can be used to power IoT devices where the device harvests energy from the environmental sources such as solar energy, vibration energy, ambient RF energy etc. Energy harvesting ensures prolonged and low maintenance operation of these devices. However, the environmental energy is completely random in nature and therefore the design of optimal energy usage techniques is desirable, which not only gives the best data rate but uses the harvested energy efficiently as well. We are working on obtaining such optimal resource allocation algorithms which can be used in future wireless networks to maximize the data rate and energy efficiency simultaneously.
Abstract: We study a wireless-powered uplink communication system with non-orthogonal multiple access (NOMA), consisting of one base station and multiple energy harvesting users. More specifically, we focus on the individual data rate optimization and fairness improvement and we show that the formulated problems can be optimally and efficiently solved by either linear programming or convex optimization. In the provided analysis, two types of decoding order strategies are considered, namely fixed decoding order and time- sharing. Furthermore, we propose an efficient greedy algorithm, which is suitable for the practical implementation of the time-sharing strategy. Simulation results illustrate that the proposed scheme outperforms the baseline orthogonal multiple access scheme. More specifically, it is shown that NOMA offers a considerable improvement in throughput, fairness, and energy efficiency. Also, the dependence among system throughput, minimum individual data rate, and harvested energy is revealed, as well as an interesting trade-off between rates and energy efficiency. Finally, the convergence speed of the proposed greedy algorithm is evaluated, and it is shown that the required number of iterations is linear with respect to the number of users.
Pub.: 27 Feb '16, Pinned: 30 Jul '17
Abstract: Energy harvesting has been developed as an effective technology for communication systems in order to extend the lifetime of these systems. In this work, we consider a singleuser energy harvesting wireless communication system, in which arrival data and harvested energy curves are modeled as continuous functions. For the single-user model, our first goal is to find an offline algorithm, which maximizes the amount of data which is transmitted to the receiver node by a given deadline. If more than one scheme exists that transmits the maximum data, we choose the one with minimum utilized energy at the transmitter node. Next, we propose an online algorithm for this system. We also consider a multi-hop energy harvesting wireless communication system in a full-duplex mode and find the optimal offline algorithm to maximize the throughput.
Pub.: 22 Jan '16, Pinned: 30 Jul '17
Abstract: Recent advances in energy-harvesting (EH) technology have enabled the realization of wireless systems composed of rechargeable devices. In this paper, we analyze the problem of maximizing the data transmission for the point-to-point (P2P) wireless communication systems which the transmitter is able to harvest energy from ambient environment. To be more general, we consider the EH optimal problem under the quasi-static frequency-selective fading channel. Our optimization work also includes energy storage loss constraint of the battery; therefore, we apply an efficient harvesting architecture, i.e., harvest-use-store (HUS), where the harvested energy is prioritized for use in data transmission. To balance the energy stored in or extracted from the battery for maximization throughput with the randomly arrival harvesting energy constraint, we first characterize the amazing properties of our optimal policy, implying a double-threshold structure of the solution, then investigate a dynamic programming (DP)-based double-layer optimal allocation policy. Further, we tend to analyze the online solution. First, the optimal policy is provided by using the continuous time stochastic dynamic programming. Then, building on the intuition from the optimal offline policy (i.e., double-threshold structure), a heuristic online policy is proposed, which is simple to be implemented. Numerical results are presented to validate the theoretical analysis and to demonstrate the superior performance over the existing counterparts in the previous literatures and show that the proposed online policies track well to the optimal solution.
Pub.: 10 Mar '15, Pinned: 30 Jul '17
Abstract: In this paper, we consider an energy harvesting (EH) node which harvests energy from a radio frequency (RF) signal broadcasted by an access point (AP) in the downlink (DL). The node stores the harvested energy in an energy buffer and uses the stored energy to transmit data to the AP in the uplink (UL). We consider a simple transmission policy, which accounts for the fact that in practice the EH node may not have knowledge of the EH profile nor of the UL channel state information. In particular, in each time slot, the EH node transmits with either a constant desired power or a lower power if not enough energy is available in its energy buffer. For this simple policy, we use the theory of discrete-time continuous-state Markov chains to analyze the limiting distribution of the stored energy for finite- and infinite-size energy buffers. Moreover, we take into account imperfections of the energy buffer and the circuit power consumption of the EH node. For a Rayleigh fading DL channel, we provide the limiting distribution of the energy buffer content in closed form. In addition, we analyze the average error rate and the outage probability of a Rayleigh faded UL channel and show that the diversity order is not affected by the finite capacity of the energy buffer. Our results reveal that the optimal desired transmit power by the EH node is always less than the average harvested power and increases with the capacity of the energy buffer.
Pub.: 08 Oct '14, Pinned: 30 Jul '17
Abstract: Energy harvesting for wireless communication networks is a new paradigm that allows terminals to recharge their batteries from external energy sources in the surrounding environment. A promising energy harvesting technology is wireless power transfer where terminals harvest energy from electromagnetic radiation. Thereby, the energy may be harvested opportunistically from ambient electromagnetic sources or from sources that intentionally transmit electromagnetic energy for energy harvesting purposes. A particularly interesting and challenging scenario arises when sources perform simultaneous wireless information and power transfer (SWIPT), as strong signals not only increase power transfer but also interference. This paper provides an overview of SWIPT systems with a particular focus on the hardware realization of rectenna circuits and practical techniques that achieve SWIPT in the domains of time, power, antennas, and space. The paper also discusses the benefits of a potential integration of SWIPT technologies in modern communication networks in the context of resource allocation and cooperative cognitive radio networks.
Pub.: 31 Aug '14, Pinned: 30 Jul '17
Abstract: In this paper, we consider wireless powered communication networks which could operate perpetually, as the base station (BS) broadcasts energy to the multiple energy harvesting (EH) information transmitters. These employ "harvest then transmit" mechanism, as they spend all of their energy harvested during the previous BS energy broadcast to transmit the information towards the BS. Assuming time division multiple access (TDMA), we propose a novel transmission scheme for jointly optimal allocation of the BS broadcasting power and time sharing among the wireless nodes, which maximizes the overall network throughput, under the constraint of average transmit power and maximum transmit power at the BS. The proposed scheme significantly outperforms "state of the art" schemes that employ only the optimal time allocation. If a single EH transmitter is considered, we generalize the optimal solutions for the case of fixed circuit power consumption, which refers to a much more practical scenario.
Pub.: 01 Mar '16, Pinned: 30 Jul '17
Abstract: The optimal resource allocation scheme in a full-duplex Wireless Powered Communication Network (WPCN) composed of one Access Point (AP) and two wireless devices is analyzed and derived. AP operates in a full-duplex mode and is able to broadcast wireless energy signals in downlink and receive information data in uplink simultaneously. On the other hand, each wireless device is assumed to be equipped with Radio-Frequency (RF) energy harvesting circuitry which gathers the energy sent by AP and stores it in a finite capacity battery. The harvested energy is then used for performing uplink data transmission tasks. In the literature, the main focus so far has been on slot-oriented optimization. In this context, all the harvested RF energy in a given slot is also consumed in the same slot. However, this approach leads to sub-optimal solutions because it does not take into account the Channel State Information (CSI) variations over future slots. Differently from most of the prior works, in this paper we focus on the long-term weighted throughput maximization problem. This approach significantly increases the complexity of the optimization problem since it requires to consider both CSI variations over future slots and the evolution of the batteries when deciding the optimal resource allocation. We formulate the problem using the Markov Decision Process (MDP) theory and show how to solve it. Our numerical results emphasize the superiority of our proposed full-duplex WPCN compared to the half-duplex WPCN and reveal interesting insights about the effects of perfect as well as imperfect self-interference cancellation techniques on the network performance.
Pub.: 16 Mar '16, Pinned: 30 Jul '17
Abstract: This paper studies a novel user cooperation method in a wireless powered communication network (WPCN), where a pair of distributed terminal users first harvest wireless energy broadcasted by one energy node (EN) and then use the harvested energy to transmit information cooperatively to a destination node (DN). In particular, the two cooperating users exchange their independent information with each other to form a virtual antenna array and transmit jointly to the DN. By allowing each user to allocate part of its harvested energy to transmit the other's information, the proposed cooperation can effectively mitigate the user unfairness problem in WPCNs, where a user may suffer from very low data rate due to the poor energy harvesting performance and high data transmission consumptions. We derive the maximum common throughput achieved by the cooperation scheme through optimizing the time allocation on wireless energy transfer, user message exchange, and joint information transmissions. Through comparing with some representative benchmark schemes, our results demonstrate the effectiveness of the proposed user cooperation in enhancing the throughput performance under different setups.
Pub.: 07 Jun '16, Pinned: 30 Jul '17
Abstract: In this paper, we consider a multiple-input multiple-output wireless powered communication network (MIMO-WPCN), where multiple users harvest energy from a dedicated power station in order to be able to transmit their information signals to an information receiving station. Employing a practical non-linear energy harvesting (EH) model, we propose a joint time allocation and power control scheme, which takes into account the uncertainty regarding the channel state information (CSI) and provides robustness against imperfect CSI knowledge. In particular, we formulate two non-convex optimization problems for different objectives, namely system sum throughput maximization and maximization of the minimum individual throughput across all wireless powered users. To overcome the non-convexity, we apply several transformations along with a one-dimensional search to obtain an efficient resource allocation algorithm. Numerical results reveal that a significant performance gain can be achieved when the resource allocation is designed based on the adopted non-linear EH model instead of the conventional linear EH model. Besides, unlike a non-robust baseline scheme designed for perfect CSI, the proposed resource allocation schemes are shown to be robust against imperfect CSI knowledge.
Pub.: 13 Sep '16, Pinned: 30 Jul '17
Abstract: Wireless-powered communications will entail short packets due to naturally small payloads, low latency requirements and/or insufficient energy resources to support longer transmissions. In this paper, a wireless-powered communication system is investigated where an energy harvesting transmitter, charged by a power beacon via wireless energy transfer, attempts to communicate with a receiver over a noisy channel. Leveraging the framework of finite-length information theory, the system performance is analyzed using metrics such as the energy supply probability at the transmitter, and the achievable rate at the receiver. The analysis yields useful insights into the system behavior in terms of key parameters such as the harvest blocklength, the transmit blocklength, the average harvested power and the transmit power. Closed-form expressions are derived for the asymptotically optimal transmit power. Numerical results suggest that power control is essential for improving the achievable rate of the system in the finite blocklength regime.
Pub.: 15 Sep '16, Pinned: 30 Jul '17