Hybrid Base Station Research Articles

Robust Resource Allocation Design for Secure IRS-Aided WPCN

This paper studies the robust resource allocation design for secure intelligent reflecting surface (IRS)-aided wireless powered communication networks (WPCN). In particular, deploying an IRS can establish favorable end-to-end radio propagation environment for achieving the desired performance gain in secure wireless-powered systems. We aim to minimize the total hybrid base station (HBS) transmit power by jointly designing the active transmitting and receiving beamforming at the HBS, the passive beamforming at the IRS, and the transmit power of each wireless-powered device (WD) and jammer node (JN). We formulate a non-convex optimization problem for the robust resource allocation design taking into account the secrecy rate requirement of the WDs and the power budgets for both the WDs and the JNs. To handle this intractable problem, we propose a computationally efficient iterative suboptimal algorithm exploiting the block coordinate descent approach, the successive convex approximation, and the penalty method, which attains a Karush-Kuhn-Tucker (KKT) solution of the transformed problem. Also, we reveal that the optimal energy beamforming matrices are rank-one sharing the same spatial direction. Simulation results unveil that the proposed scheme is able to dramatically reduce the HBS transmit power over various baseline schemes adopting existing solutions. Besides, our results show the superiority of introducing IRS for secure communication in wireless-powered systems.

RF Energy Harvesting Wireless Networks: Challenges And Opportunities

Energy harvesting wireless networks is one of the most researched topics in this decade, both in industry and academia, as it can offer self-sustaining sensor networks. With RF energy harvesting (RF-EH) embedded, the sensors can operate for extended periods by harvesting energy from the environment or by receiving it as an Energy signal from a hybrid base station (HBS). Thus, providing sustainable solutions for managing massive numbers of sensor nodes. However, the biggest hurdle of RF energy is the low energy density due to spreading loss. This paper investigates the RF-EH node hardware and design essentials, performance matrices of RF-EH. Power management in energy harvesting nodes is discussed. Furthermore, an information criticality algorithm is proposed for critical and hazardous use cases. Finally, some of the RF-EH applications and the opportunities of 5G technologies for the RF-EH are introduced.

RF Energy Harvesting Wireless Networks: Challenges And Opportunities

Energy harvesting wireless networks is one of the most researched topics in this decade, both in industry and academia, as it can offer self-sustaining sensor networks. With RF energy harvesting (RF-EH) embedded, the sensors can operate for extended periods by harvesting energy from the environment or by receiving it as an Energy signal from a hybrid base station (HBS). Thus, providing sustainable solutions for managing massive numbers of sensor nodes. However, the biggest hurdle of RF energy is the low energy density due to spreading loss. This paper investigates the RF-EH node hardware and design essentials, performance matrices of RF-EH. Power management in energy harvesting nodes is discussed. Furthermore, an information criticality algorithm is proposed for critical and hazardous use cases. Finally, some of the RF-EH applications and the opportunities of 5G technologies for the RF-EH are introduced.

Evolutionary computation technique enhancing the performance of cognitive radio networks with energy harvesting

The intervention of evolutionary computation methods in studying energy harvesting (EH) techniques in multiple-input-single-output cognitive radio networks (MISO-CRNs) is carefully investigated. In this work, a secondary user (SU) with multiple antennas harvests energy from a hybrid base station (HBS) in addition to harvesting from the primary user (PU) transmission during the downlink time-slot. Hence, the SU transmits its data on the uplink over Nakagami-m fading channels. For the underlay paradigm, a specific tolerable PU interference limits the SU total transmission power. The HBS does not have previous information about the SU battery level. A closed-form expression for the SU exact outage probability is derived and simplified to its asymptotic formula for the high signal-to-noise-ratio (SNR) region. Closed-form expressions for the system average symbol error probability (ASEP) and ergodic capacity are obtained. The particle swarm optimization (PSO) algorithm is used to find the optimal SU transmission power to minimize the sophisticated formula of the exact outage probability. Simulations and numerical results reveal the effect of the critical system parameters on the overall system performance and validate the derived mathematical analysis. Moreover, the optimum solution of the power optimization problem shows noteworthy enhancement of the system performance compared to the traditional equally distributed model.

Cooperative Jamming-Aided Secure Wireless Powered Communication Networks: A Game Theoretical Formulation

This letter investigates a secure wireless powered communication network (WPCN). Specifically, a cooperative jamming node collects power from a hybrid base station (HBS) which introduces additional interference to degrade the reception of the eavesdroppers. In order to consider a more practical scenario, we formulate a Stackelberg game to pursue the maximum revenues of the HBS and the jamming node. For the formulated game, we derive a closed-form expression for the jamming power allocation and the jamming price to achieve the Stackelberg equilibrium. Simulation results are presented to verify the theoretical derivations of our proposed scheme. Moreover, it is shown that our proposed scheme is superior to the benchmark scheme in terms of the secure performance.

MmWave Multiuser MIMO Precoding With Fixed Subarrays and Quantized Phase Shifters

Millimeter-wave (mmWave) wireless communication promises high data-rates when combined with multiuser multiple-input multiple-output (MU-MIMO) technology. A practical deployment of these technologies, however, faces numerous challenges, including the design of energy-efficient analog hardware. To address these challenges, we consider a hybrid base station architecture that consists of a set of fixed subarrays with quantized phase shifters (FS-QPS). For this system, we investigate the multiuser beamforming gains with different phase-quantization levels and subarray geometries. We show that for zero forcing baseband precoding, analog precoder optimization becomes an eigenvalue maximization problem, which can be approximated efficiently by received power maximization. We develop an efficient, optimal analog precoder for well-established mmWave channel models, and provide performance bounds characterizing the required phase-shifting accuracy for a beam-steering codebook as a function of the geometric size of the subarray. To demonstrate the efficacy of the proposed FS-QPS architecture, we show simulation results using the latest 3GPP mmWave channel model for multiuser spectral efficiency, and compare our solution to existing architectures.

Secrecy Throughput Optimization for the WPCNs With Non-Linear EH Model

This paper investigates secure communication from a wireless-powered transmitter to a desired receiver with multiple eavesdroppers in the wireless powered communication networks (WPCNs). Considering the non-linear energy harvesting (EH) model, we propose a secure two-phase communication protocol with the help of a hybrid base station (HBS). First, in the power transfer (PT) phase, the HBS transfers wireless power to the transmitter. Then in the subsequent secure information transmission (SIT) phase, the transmitter sends the secret information using the energy harvested in the PT, under the protection of artificial noise (AN) generated by the HBS. First, based on this communication protocol, we maximize the secrecy throughput with perfect channel information state (CSI) under the transmit power constraint at the HBS. The secrecy throughput maximization (STM) problem is non-convex, and hence we reformulate it by exploiting the primal decomposition method (PDM) to obtain tractable forms. The PDM-based transmit scheme (PDM-TS) is proposed for the STM. In addition, considering the imperfect CSI of wiretap channel, we further design the robust transmit scheme for the worst-case secrecy throughput maximization (wSTM) problem. Since the wSTM shows high non-convexity, we extend the PDM by combining it with the S -procedure, and the PDM-based robust transmit scheme (PDM-RTS) is proposed for the wSTM. Finally, the numerical simulations are provided to show the effectiveness of the proposed transmit schemes.

Secure Wireless Powered and Cooperative Jamming D2D Communications

This paper investigates a secure wireless-powered device-to-device (D2D) communication network in the presence of multiple eavesdroppers, where a hybrid base station (BS) in a cellular network not only provides power wirelessly for the D2D transmitter to guarantee power efficiency for the D2D network, but also serves as a cooperative jammer (CJ) to interfere with the eavesdroppers. The cellular and D2D networks can belong to different service providers, which means that the D2D transmitter would need to pay for the energy service released by the hybrid BS to guarantee secure D2D communication. In order to exploit the hierarchical interaction between the BS and the D2D transmitter, we first formulate a Stackelberg game based energy trading scheme, where the quadratic energy cost model is considered. Then, a non-energy trading based Stackelberg game is investigated to study the reversed roles of the BS and the D2D users. For comparison, we also formulate and resolve the social welfare optimization problem. We derive the closed-form Stackelberg equilibriums of the formulated games and the optimal solutions for the social welfare optimization problem. Simulation results are provided to validate our proposed schemes to highlight the importance of energy trading interaction between cellular and D2D networks.

Multi-Dimensional Resource Allocation for Uplink Throughput Maximisation in Integrated Data and Energy Communication Networks

The interdisciplinary research of the radio-frequency (RF) signal-based wireless power and information transfer is expected to address the energy shortage issue in the massively deployed low-power Internet of Things devices. Different from conventional wireless powered communication networks (WPCNs), the hybrid base station (H-BS) adopts the simultaneous wireless information and power transfer (SWIPT) for the sake of satisfying the downlink data and energy requests of the multiple user equipments (UEs). The energy harvested from the downlink transmissions can be depleted for supporting the UEs’ uplink transmissions. Integrating SWIPT in the downlink transmission of the WPCN yields a generic integrated data and energy communication network, where the H-BS is equipped with multiple antennas and both the downlink and uplink transmissions are slotted in the time-domain. Furthermore, both the sum-throughput and the fair-throughput of the uplink transmissions are maximized by jointly optimizing the transmit beamformer of the H-BS in the spatial-domain, the time-slot allocation in the time-domain and the signal splitting strategies of the UEs in the power domain, while satisfying the UEs’ minimum downlink transmission requirements. Due to the non-convexity of the problem, a low-complexity successive convex approximation-based algorithm is relied upon for obtaining the optimal resource allocation scheme in the time-domain, power-domain, and spatial-domain. The numerical results validate the efficiency of our proposed resource allocation algorithm and they also demonstrate that supporting low-rate data services during the downlink transmissions does not degrade the wireless power transfer and hence does not reduce the uplink throughput.

Power Allocation Scheme and Performance Analysis for Multiuser Underlay Full-Duplex Cognitive Radio Networks With Energy Harvesting

This paper introduces a comprehensive wireless energy harvesting model applied for multiple secondary users (SUs) in full-duplex cognitive radio networks. In this proposed model, SUs harvest energy from a hybrid base station (HBS), in addition to the primary user (PU) network on the downlink and transmit their data on the uplink. The opportunistic user selection scheme is employed in the SU network to achieve a better SU performance. Considering the underlay spectrum sharing paradigm, the total SU transmitted powers are limited to the maximum allowable PU interference threshold. Moreover, the proposed SU system suffers from self-interference from the transmitting antenna of the HBS and co-channel interference from the PU transmitter. Closed-form expressions for the SU system outage probability, average symbol error probability, and ergodic capacity are derived. Obtained exact expressions are then simplified to their asymptotic results in the high signal-to-noise-ratio regime. Based on these results, a power allocation optimization problem is formulated to reduce the SU outage probability under the constraints of performance indices. Computer-aided numerical and simulation work is performed to validate the exact expressions.

Distributed Power Control Schemes for In-Band Full-Duplex Energy Harvesting Wireless Networks

This paper studies two power control problems in energy harvesting wireless networks where one hybrid base station (HBS) and all user equipments (UEs) are operating in in-band full-duplex mode. We consider minimizing the aggregate power subject to the quality of service requirement constraint, and maximizing the aggregate throughput. We address these two problems by proposing two distributed power control schemes for controlling the uplink transmit power by the UEs and the downlink energy harvesting signal power by the HBS. In our proposed schemes, the HBS updates the downlink transmit power level of the energy-harvesting signal so that each UE is enabled to harvest its required energy for powering the operating circuit and transmitting its uplink information signal with the power level determined by the proposed schemes. We show that our proposed power control schemes converge to their corresponding unique fixed points starting from any arbitrary initial transmit power. We will show that our proposed schemes well address the stated problems, which is also demonstrated by our extensive simulation results.

Cost-Constrained Viterbi Algorithm For Resource Allocation in Solar Base Stations

Solar energy is currently a popular renewable resource, yet limited daily. In green cellular networks, multiple constraints optimization (MCO) problems arise naturally. For example, a typical objective is to control the power transmission of the hybrid base stations (BSs) (connected to both solar panels and electrical grid) in order to maximize user’s average throughput, under the constraints of consumed grid energy and user’s blocking rate. However, such problems have been generally proved to be NP-hard. In this paper, we formulate this generic MCO problem as a quantized Markovian cost-reward model, with no assumption on input data. We then propose a novel algorithm, namely cost-constrained Viterbi algorithm, which recursively returns the optimal policy with linear computational complexity for this model. As an application, we provide engineering rules for the design of hybrid BSs through extensive simulations. In comparison with brute force method for a simple scenario, we find that our algorithm does achieve the constrained optimal policy.

Wireless Power Transfer and Cooperative Jamming for Secrecy Throughput Maximization

This letter studies the secure communication between a wireless powered source node and a destination node in the presence of multiple eavesdroppers. We propose a hybrid base station (BS) scheme where the hybrid BS first transfers wireless power to the source and then performs cooperative jamming while the source transmits the information signal using the harvested energy. We maximize the secrecy throughput by jointly optimizing the time allocation, source transmit power, and redundancy rate under the secrecy constraint and transmit power constraint. We transform the secrecy throughput maximization problem into a convex optimization problem and obtain the optimal solutions efficiently. Numerical results illustrate that our solution is superior to other benchmark schemes.

Internetworking VCSEL-Based Hybrid Base Station Towards Simultaneous Wireless and Wired Transport for Converged Access Network

A hybrid base-station (H-BS) scheme that has the potential to establish intercommunications among neighboring access nodes without sending the signals to the edge node to simultaneously transport wireless and wireline services to integrated access nodes is proposed. As the scheme uses vertical-cavity surface-emitting lasers as the light source in the H-BS, it can potentially be realized at low cost without any temperature control.

Laser-free inter-networking hybrid base stations towards convergence of wireless and wired access networks

A laser-free base station scheme that can be integrated with an optical network unit for overlaying the transport of wireless signals in an optical access network is proposed and experimentally demonstrated. It is shown that this scheme has the potential to establish inter-communication among neighbouring base stations to provide simultaneous access to wireless and wired services.