Cognitive Wireless Powered Communication Networks Research Articles

Achievable Rates and Resource Allocation for CDMA-Based Overlay Cognitive Radio With RF Energy Harvesting

This article introduced a cognitive wireless powered communication network with an uplink (UL) code-division multiple access (CDMA) scheme consisting of one hybrid access point (H-AP) and multiple energy harvesting secondary users (SUs), which are coexisted with a primary wireless network. The frame structure is coordinated through the two-phase harvest-then-transmit protocol. The energy-limited SUs first harvest wireless energy in the downlink phase and then transmit their information signals simultaneously to H-AP with the CDMA scheme in the UL phase. An overlay spectrum sharing model is also considered where H-AP has access to the primary transmitter's codebook and primary network's channel. Our goal is to maximize the sum-throughput optimization problem of SUs via jointly optimizing power and time allocation. The considered joint optimization problem is generally nonconvex due to coupled variables. As a solution, we first transform it into the equivalent convex form using proper variables and then we solve it using the convex optimization technique. The closed-form solutions for time and power allocations are given. We also confirm from various simulations’ results that our proposed CDMA scheme is superior to the conventional time-division multiple access schemes.

Intelligent Reflecting Surfaces for Sum-Rate Maximization in Cognitive Radio Enabled Wireless Powered Communication Network

In this paper, we study a cognitive radio (CR)-enabled wireless powered communication network (WPCN) with an intelligent reflecting surface (IRS). A cognitive wireless powered communication network (CWPCN) consisting of one secondary wireless powered communication network, in which a hybrid access point broadcasts wireless energy to multiple users on downlink and receives information signals on uplink, shares the same spectrum with the existing primary wireless communication network. In this paper, we consider an underlay CWPCN in which the secondary network is regulated by a given interference temperature constraint (ITC) such that interference with the primary network is kept no greater than a predefined threshold. To enhance the performance of the CWPCN, we consider an IRS-assisted network in which multiple passive reflection elements are configured to reflect the signals in any desired phase/direction. Our main goal is to maximize the sum throughput of secondary users while managing the interference constraint. For this, we jointly optimize the uplink and downlink phase shift matrices of the IRS elements with optimal time slots for wireless energy transfer (WET) on downlink and wireless information transfer on uplink. In finding the optimal solution, the formulated optimization problem is non-convex, complex, and intractable. In this paper, we propose an alternating optimization (AO)-based solution with a successive convex approximation (SCA) technique. We show through simulation results that the proposed IRS-assisted network provides a significant enhancement in performance over the conventional CWPCN.

Full-duplex overlay cognitive wireless powered communication network using RF energy harvesting

Full-duplex overlay cognitive wireless powered communication network using RF energy harvesting

Fuzzy Based Cluster Greedy Optimization and Convolutional Neural Networks Based Scheme for Internet of Medical Things Based Healthcare Resource Allocation in Cognitive Wireless Powered Communication Network

A cognitive wireless powered communication network (CWPCN) for spectrum distribution in IoMT based healthcare systems is employed with a principal network, which in turn deals with security issues from various attacks like Denial of Service (DoS), Man-In-the-Middle, or phishing attacks. In this, a new protocol is proposed for wireless powered SU (secondary users) so as to cooperate with PU (primary user) of the healthcare network. At the time of wireless power transfer (WPT) in a IoMT based healthcare network, the first harvest energy of SUs was carried from power signals broadcasted by the cognitive hybrid access point. Then the harvested energy is employed while gaining transmission opportunities simultaneously all through the phase of Wireless Information Transfer (WIT) of healthcare system. Furthermore, Fuzzy based cluster greedy algorithm is introduced for reducing the interruption of PU secrecy prospect and to offer the best optimal values in the healthcare data. In this approach, the injection impact and reactive jamming attacks on wireless transmission are analyzed. These can be recognized through a Convolutional Neural Network (CNN) to detect different attack types and classify them. Finally, the results were compared with the existing method.

Performance Analysis of Cognitive Wireless Powered Communication Networks Under Unsaturated Traffic Condition

By improving the efficiency of wireless power transfer (WPT), wireless powered communication networks (WPCNs) are receiving increasing attention. WPCN provides untethered mobility and prolongs the network lifetime by eliminating the need for repetitive charging and replacement of the battery. In this paper, we consider a cognitive WPCN in which wireless powered secondary users (SUs) opportunistically exploit the spectrum licensed to the primary users (PUs). Each SU is associated with a power beacon (PB) node which is responsible for charging the corresponding SU and receiving its data over different frequency bands. SUs have unsaturated data traffic and can transmit if they are out of any guard zone which is defined around active PUs to prevent strong interference. Using tools from stochastic geometry and queueing theory, we characterize the effects of the randomness in data and energy availability of SUs on the interference among PUs and SUs. Then, we derive the service time distribution, mean waiting time, and queue stability criterion for a typical SU, as well as the outage probability of a typical PU. Finally, through extensive simulations, the analytical results are evaluated and the effects of different parameters on the network performance are studied.

Sum‐throughput maximization for overlay cognitive wireless powered network with energy harvesting capability

AbstractIn this article, a novel time division multiple access (TDMA)‐based approach for optimal resource allocation in an overlay cognitive wireless powered communication network is proposed. In this network, power in the secondary network (SN) is provided by the primary network (PN) in addition to its own wireless network. Using the TDMA and a harvest‐then‐transmit protocol, the time and power allocation for downlink wireless energy transfer (WET) and uplink wireless information transmission (WIT) are jointly optimized to maximize the sum‐throughput in SN. Quality of service in PN and power and time in SN, as the main constrains are considered for sum‐throughput maximization in this network. This is a non‐convex problem which gets converted to a convex problem using active interference‐temperature control technique. Moreover, a new closed‐form expression which results in sub‐optimal power and time‐allocation (SO‐PT‐A) is addressed. The performance of proposed algorithm is compared with the equal time allocation (ETA) and fixed TDMA‐allocation (FTDMA‐A) algorithms which impose some special constraints for optimal power and time allocation. The simulation results depict that the SO‐PT‐A algorithm outperforms the ETA and FTDMA‐A algorithms. Eventually, the performance of the SO‐PT‐A algorithm is evaluated with other well‐known algorithms considering different values of the average and maximum transmit power of the hybrid‐access point (H‐AP), the number of secondary users (SUs) and path loss exponent.

Resource Allocation for Secure Communications in Cooperative Cognitive Wireless Powered Communication Networks

We consider a cognitive wireless powered communication network sharing the spectrum with a primary network, which faces security threats from eavesdroppers (EAVs). We propose a new cooperative protocol for the wireless powered secondary users (SUs) to cooperate with the primary user (PU). In the protocol, the SUs first harvest energy from the power signals transmitted by the cognitive hybrid access point during the wireless power transfer phase, and then use the harvested energy to interfere with the EAVs and gain transmission opportunities at the same time during the wireless information transfer phase. Taking the maximization of the SU ergodic rate as the design objective, resource allocation algorithms based on the dual optimization method and the block coordinate descent method are proposed for the cases of perfect channel state information (CSI) and collusive/non-collusive EAVs under the PU secrecy constraint. More PU favorable greedy algorithms aimed at minimizing the PU secrecy outage probability are also proposed. We furthermore consider the unknown EAVs' CSI case and propose an efficient algorithm to improve the PU security performance. Extensive simulations show that our proposed protocol and corresponding resource allocation algorithms can not only let the SU gain transmission opportunities but also improve the PU security performance even with unknown EAVs' CSI.

Sum-Throughput Maximization of Secondary Users in an In-Band Full-Duplex Cognitive Wireless Powered Communication Network

This paper studies a cognitive wireless powered communication network (CWPCN). Such a network consists of some distributed secondary users (SUs) and a hybrid access point (H-AP) as a secondary network which is in the vicinity of a primary network. In this model, H-AP and SUs can operate in two modes which are an in-band full-duplex (I-FD) mode and the half-duplex (HD) mode. In the former mode, the network is called FD-CWPCN-FD while for the latter mode the HD-CWPCN-HD is used. An underlay spectrum sharing model is also considered. The goal is to maximize the sum-throughput of SUs by optimal selection of allocated time and energy to SUs in both I-FD and HD modes. By using convex optimization techniques and proposing an algorithm that is called H-AP-based joint optimal time and power allocation, we obtain the closed-form expressions for the optimal allocated time and energy. Numerical results illustrate when the transmitted power from H-AP is low or self-interference cancellation in H-AP is more accurate, FD-CWPCN-FD has higher sum-throughput than HD-CWPCN-HD.

Optimizing throughput fairness of cluster-based cooperation in underlay cognitive WPCNs

In this paper, we consider a secondary wireless powered communication network (WPCN) underlaid to a primary point-to-point communication link. The WPCN consists of a multi-antenna hybrid access point (HAP) that transfers wireless energy to a cluster of low-power wireless devices (WDs) and receives sensing data from them. To tackle the inherent severe user unfairness problem in WPCN, we consider a cluster-based cooperation where a WD acts as the cluster head that relays the information of the other WDs. Besides, we apply energy beamforming technique to balance the dissimilar energy consumptions of the WDs to further improve the fairness. However, the use of energy beamforming and cluster-based cooperation may introduce more severe interference to the primary system than the WDs transmit independently. To guarantee the performance of primary system, we consider an interference-temperature constraint to the primary system and derive the throughput performance of each WD under the peak interference-temperature constraint. To achieve maximum throughput fairness, we jointly optimize the energy beamforming design, the transmit time allocation among the HAP and the WDs, and the transmit power allocation of each WD to maximize the minimum data rate achievable among the WDs (the max-min throughput). We show that the non-convex joint optimization problem can be transformed to a convex one and then be efficiently solved using off-the-shelf convex algorithms. Moreover, we simulate under practical network setups and show that the proposed method can effectively improve the throughput fairness of the secondary WPCN, meanwhile guaranteeing the communication quality of the primary network.

Cooperative resource allocation in cognitive wireless powered communication networks with energy accumulation and deadline requirements

This study investigates a multi-carrier cognitive wireless powered communication network (CWPCN)with a wirelessly powered primary user (PU).A two-stage cooperative protocol between the PU and the secondaryuser (SU) is adopted so that the PU can harvest energy from the SU while the SUgains transmission opportunities. It is assumed that the energy harvestedby the PU can be accumulated for future usage, and the quality of service of the PU is guaranteed by satisfying the required minimum number of data bitsfor a given deadline. Herein, we maximize the SU rate by considering the time allocation, subcarrier allocation, and power allocation in both an offlinesetting (in which the future channel gains are known a priori) and an onlinesetting (in which only the current channel gains are known). In the offline and online schemes, the maximizationproblem is solved using the block-coordinate descent method and the Lagrangeduality method. The effectiveness of theproposed schemes is evaluated and verified via simulation experiments against benchmark schemes.

Resource allocation in cognitive wireless powered communication networks with wirelessly powered secondary users and primary users

Resource allocation in cognitive wireless powered communication networks with wirelessly powered secondary users and primary users

Cognitive wireless powered communication networks with secondary user selection and primary QoS constraint

In this research, the authors investigate the outage probability (OP) of the secondary network in a cognitive wireless powered communication network. Energy-constrained secondary users harvest energy from a hybrid access-point (H-AP) and the primary transmitter in the first phase. In the second phase, they select a secondary user based on two different schemes, namely the best uplink channel selection (UCS) and the minimal interference channel selection (MICS), to transfer information to the H-AP. The secondary network can share the same spectrum with the primary network ensuring that a desired OP constraint in the primary network is always met. This constraint represents the quality-of-service (QoS) of the primary network. The analytical expressions and asymptotic expressions of the OP of the secondary network are derived. The result shows that increasing the number of secondary users can considerably improve system performance. The transmit power of the selected secondary user, energy harvesting time and relaxing the QoS constraint of the primary network have a significant impact on the OP of the secondary network. The results show that UCS outperforms MICS.

Throughput Maximization for Hybrid Backscatter Assisted Cognitive Wireless Powered Radio Networks

In this paper, we consider a cognitive wireless powered communication network for Internet of Things applications, which consists of a primary communication pair and a secondary communication system. We propose a novel hybrid harvest-then-transmit (HTT) and backscatter communication (BackCom) mode for the information transmission of the secondary communication system. When the primary channel is busy, cognitive users (CUs) backscatter the incident signal from the primary transmitter to the information receiver in the ambient backscatter (AB) mode or harvest energy for the future information transmission. When the primary channel is idle, CUs backscatter the incident signal from the power beacon in the bistatic scatter (BS) mode or work in the HTT mode to transmit information. We further investigate the optimal time allocation between the AB mode and energy harvesting and that between the BS mode and the HTT mode for the sake of maximizing the throughput of the secondary communication system, and derive the numerical solutions. To be specific, we derive the closed-form optimal solution for a single CU case, and moreover, obtain the optimal combination of the working modes. Numerical results demonstrate the advantage of our proposed hybrid HTT and BackCom mode over the benchmark mode in terms of system throughput.

Proportional Fairness in Cognitive Wireless Powered Communication Networks

In this letter, we consider a cognitive wireless powered communication network (CWPCN), with a secondary wireless powered communication network (WPCN) that has cognitive ability to coexist with a primary communication network. To tackle the unfairness resource allocation issue in CWPCN, we extend proportional fair scheduler to this category of network. By utilizing the time division-based “harvest-then-transmit” protocol, we establish an optimization problem for optimal time slot allocation, which maximizes the bandwidth utility function for proportional fairness, under the constraints of time and interference. To solve this problem, an algorithm is proposed to find a tradeoff between fairness and throughput. Simulation results confirm the positive effect on the promotion of fairness metric.

Sum Throughput Maximization for Multi-User MIMO Cognitive Wireless Powered Communication Networks

In this paper, we study multi-user multi-input multi-output cognitive wireless powered communication networks (WPCN), in which a secondary WPCN shares spectrum with a primary wireless information transfer system. A typical WPCN consists of two different phases. In the first downlink phase, a hybrid access point (H-AP) transfers energy to charge users, and then in the subsequent uplink phase, the users send information by using the harvested energy to the H-AP. We consider two different cognitive WPCN protocols depending on the cooperation level between the primary transmitter and the secondary H-AP. For both cases, we formulate sum throughput maximization problems by taking the interference leakage to the primary network into consideration. The problems are generally non-convex due to coupled variables in the WPCN. To tackle this issue, we first convert the problems into equivalent convex forms, and then identify the global optimal solutions by applying the proposed iterative optimization algorithms. Finally, the simulation results demonstrate that the proposed algorithms outperform conventional schemes.

Energy-Efficient Cooperation in Cognitive Wireless Powered Networks

In this letter, we consider a cooperative sharing model for cognitive wireless powered communication networks (CWPCNs), which leverages the notion of cooperation between primary and secondary systems in cognitive radio networks to accomplish primary transmission early and vacate opportunity for secondary transmission. With the proposed spectrum sharing model, we investigate the optimal design for such a cooperative CWPCN with both amplify-and-forward (AF) and decode-and-forward (DF) protocols to maximize its uplink energy efficiency. The energy efficiency optimization problem is decomposed into two subproblems for uplink scheduling and cooperative power control. We also propose a suboptimal solution to tackle the unavailable information on channel condition between the primary transmitter and secondary users. The numerical results show that the DF protocol outperforms the AF protocol in general and the suboptimal solution is slightly outperformed by the optimal one.

Cognitive Wireless Powered Network: Spectrum Sharing Models and Throughput Maximization

The recent advance in radio-frequency (RF) wireless energy transfer (WET) has motivated the study of wireless powered communication network (WPCN) in which distributed wireless devices are powered via dedicated WET by the hybrid access-point (H-AP) in the downlink (DL) for uplink (UL) wireless information transmission (WIT). In this paper, by utilizing the cognitive radio (CR) technique, we study a new type of CR enabled secondary WPCN, called cognitive WPCN, under spectrum sharing with the primary wireless communication system. In particular, we consider a cognitive WPCN, consisting of one single H-AP with constant power supply and distributed wireless powered users, shares the same spectrum for its DL WET and UL WIT with an existing primary communication link, where the WPCN’s WET/WIT and the primary link’s WIT may interfere with each other. Under this new setup, we propose two coexisting models for spectrum sharing of the two systems, namely underlay - and overlay -based cognitive WPCNs, depending on different types of knowledge on the primary user transmission available for the cognitive WPCN. For each model, we maximize the sum-throughput of the cognitive WPCN by optimizing its transmission under different constraints applied to protect the primary user transmission. Analysis and simulation results are provided to compare the sum-throughput of the cognitive WPCN versus the achievable rate of the primary user under two proposed coexisting models. It is shown that the overlay based cognitive WPCN outperforms the underlay based counterpart, thanks to its fully co-operative WET/WIT design with the primary WIT, while also requiring higher complexity for implementation.