Tran Khai Hoan (K18 HCM) (original) (raw)
Papers by Tran Khai Hoan (K18 HCM)
Proceedings of the 2019 2nd International Conference on Electronics, Communications and Control Engineering
Conventionally, to investigate the aging effects in analog-circuit-design phase, it requires to s... more Conventionally, to investigate the aging effects in analog-circuit-design phase, it requires to simulate, modify and verify iteratively on a number of circuit samples. In this work, we propose a fast aging simulation scheme for analog circuit modification and verification process based on the delta model in which the delta circuits are made from the delta devices built with the aging effect models by Verilog-A. During simulation, the aging device parameters are also updated continuously to attain the same accuracy with works in the literature; however, we only simulate the signal-difference between two similar circuits by re-using the previous simulation results to accelerate the aging simulation process. The experiment results show that, in the scenario of channel hot carrier effect on an analog amplifier circuit, the aging simulation process of the proposed scheme can be sped-up 10 times compared to that of conventional scheme with almost the same accuracy.
Proceedings of the 3rd International Conference on Electronics, Communications and Control Engineering
Herein, we propose a fast yield estimation approach for analog circuits design in which we combin... more Herein, we propose a fast yield estimation approach for analog circuits design in which we combine the behavioral model of circuit and the Quasi-Monte Carlo (QMC) sampling technique to accelerate yield estimation process. The behavioral model is constructed in Verilog-A based on the simulation results which are done at transistor-level; then, the accuracy of the model is verified by experimental testing on a specific analog circuit. Furthermore, instead of using random circuit samples, in this work, QMC circuit samples are adopted to obtain faster convergence rates for the yield prediction process. In conventional analog design stage, designers repeat a number of yield estimation process to select the optimal design point. Each yield estimation effort is a time-consuming process since designers have to simulate on a large number of circuits. Unlike the conventional method, in this work, we build a look-up table for constructing behavioral model of any given circuit; then, this table can be reused in repeating the yield-estimation processes. Therefore, the proposed method can significantly reduce the time for the yield estimation process. Experimental results show that the proposed approach can speed-up the yield estimation process 8 times compared to conventional simulation-based methods with a reasonable drop in accuracy (less than 5%).
Wireless Networks, 2021
Non-orthogonal multiple access (NOMA) is one of the promising techniques for spectrum efficiency ... more Non-orthogonal multiple access (NOMA) is one of the promising techniques for spectrum efficiency in wireless networks. In this paper, we consider an uplink NOMA cognitive system, where the secondary users (SUs) can jointly transmit data to the cognitive base station (CBS) over the same spectrum resources. Thereafter, successive interference cancellation is applied at the CBS to retrieve signals transmitted by the SUs. In addition, the energy-constrained problem in wireless networks is taken into account. Therefore, we assume that the SUs are powered by a wireless energy harvester to prolong their operations; meanwhile, the CBS is equipped with a traditional electrical supply. Herein, we propose an actor–critic reinforcement learning approach to maximize the long-term throughput of the cognitive network. In particular, by interacting and learning directly from the environment over several time slots, the CBS can optimally assign the amount of transmission energy for each SU according...
IEEE Access, 2021
The performance of data aggregation in industrial wireless communications can be degraded by envi... more The performance of data aggregation in industrial wireless communications can be degraded by environmental interference on Industrial Scientific Medical (ISM) channels. In this paper, the opportunistic spectrum access capability of cognitive radio (CR) was applied to enable devices to share primary channels with the aim of enhancing the transmission performance of the WirelessHART network. We considered a linear convergecast network, where the packets generated at each device were routed to the gateway (GW) through the aid of neighboring devices. The solar-powered cognitive access points (CAPs) were deployed to improve the successful transmission probability of the packets among field devices by opportunistically allocating the primary channels to the devices for data transmissions. In this paper, we formulate the scheduling problem of long-term throughput maximization as a framework of a Markov decision process by considering the constraints of the minimum delay, the number of required ISM channels, and the harvested energy at the CAPs. Then, we propose a deep reinforcement learning-based scheduling scheme to optimally assign multiple ISM and primary channels to the field devices in each superframe to maximize the received packets at the GW. The simulation results confirmed the superiority of the proposed scheme compared to existing methods. INDEX TERMS wirelessHART, cognitive radio, markov decision process, industrial scientific medical
Applied Sciences, 2020
Non-orthogonal multiple access (NOMA) is considered a potential technique in fifth-generation (5G... more Non-orthogonal multiple access (NOMA) is considered a potential technique in fifth-generation (5G). Nevertheless, it is relatively complex when applying NOMA to a massive access scenario. Thus, in this paper, a hybrid NOMA/OMA scheme is considered for uplink wireless transmission systems where multiple cognitive users (CUs) can simultaneously transmit their data to a cognitive base station (CBS). We adopt a user-pairing algorithm in which the CUs are grouped into multiple pairs, and each group is assigned to an orthogonal sub-channel such that each user in a pair applies NOMA to transmit data to the CBS without causing interference with other groups. Subsequently, the signal transmitted by the CUs of each NOMA group can be independently retrieved by using successive interference cancellation (SIC). The CUs are assumed to harvest solar energy to maintain operations. Moreover, joint power and bandwidth allocation is taken into account at the CBS to optimize energy and spectrum efficie...
IOP Conference Series: Materials Science and Engineering, 2021
In this paper, we present the design of a low-cost remote monitoring and control network for hous... more In this paper, we present the design of a low-cost remote monitoring and control network for household cultivation, in which peripherals connected to each sensor-node can be re-configured remotely from the internet via a master node without any changing on the system firmware. The feasibility of the proposed scheme is evaluated via experiments. Particularly, the experiments set-up consists of one master node communicating wirelessly with some sensor nodes (slaves) to collect sensing data or send commands to them to manage the operating of the system. The sensing data from slaves will be collected and updated periodically to Google Sheets by master node via the internet connection. Additionally, slaves are equipped with versatile ports for connecting with sensors. The port is designed to be compatible with most popular communication standards such as analog, digital, I2C, UART, SPI. The key design of these communication ports is that when plugging/unplugging a sensor into/from a port, the corresponding slave can be re-configured directly on Google Sheets or keypad connected to master node. The research results can be further extended and improved to be applicable to household cultivation as well as application models of smart agriculture.
Electronics, 2020
Currently, deploying fixed terrestrial infrastructures is not cost-effective in temporary circums... more Currently, deploying fixed terrestrial infrastructures is not cost-effective in temporary circumstances, such as natural disasters, hotspots, and so on. Thus, we consider a system of caching-based UAV-assisted communications between multiple ground users (GUs) and a local station (LS). Specifically, a UAV is exploited to cache data from the LS and then serve GUs’ requests to handle the issue of unavailable or damaged links from the LS to the GUs. The UAV can harvest solar energy for its operation. We investigate joint cache scheduling and power allocation schemes by using the non-orthogonal multiple access (NOMA) technique to maximize the long-term downlink rate. Two scenarios for the network are taken into account. In the first, the harvested energy distribution of the GUs is assumed to be known, and we propose a partially observable Markov decision process framework such that the UAV can allocate optimal transmission power for each GU based on proper content caching over each flig...
IEEE Sensors Journal, 2019
Physical layer wireless communications are more and more essential, and are vulnerable to malicio... more Physical layer wireless communications are more and more essential, and are vulnerable to malicious users owing to the nature of broadcast channels. Herein, we consider a centralized multi-channel cognitive radio network in the presence of eavesdroppers (EVEs). In the network, the secondary base station (SBS) shares currently free primary channels to simultaneously communicate with secondary users (SUs), while passive eavesdroppers attempt to overhear data in the secondary communications. Each limited-battery SU is equipped with two antennas (one for transmitting signals, and other for receiving signals) and is powered by a solar energy harvester. Meanwhile, the SBS equipped with multiple antennas can operate in full-duplex (FD) transmission mode (simultaneously transmit and receive signals) or in half-duplex (HD) transmission mode (transmit and receive signals in turn during each half of a time slot) with the SUs. In this paper, we propose a novel scheme to maximize the secondary system security of the multi-channel cognitive system in the presence of multiple passive EVEs, in which the EVEs are able to overhear the data of the SBS−SU transmissions on all the primary channels. The problem of decision making is formulated as the framework of a partially observable Markov decision process (POMDP), and an optimal solution is achieved by adopting value iteration−based dynamic programming. Specifically, in each time slot, the SBS allocates optimal channel and optimal action (i.e. either stay silent or employ HD/FD transmission modes with optimal transmission power) for each SU in order to obtain maximum long-term secrecy rate for the secondary system.
International Journal of Communication Systems, 2019
Wireless energy harvesting enables wireless-powered communications to accommodate data services i... more Wireless energy harvesting enables wireless-powered communications to accommodate data services in a self-sustainable manner over a long operational time. Along with energy harvesting, an ambient backscatter technique helps a secondary transmitter reflect existing radio frequency (RF) signal sources to communicate with a secondary receiver when the primary channel (PC) is utilized. However, secondary system performance is significantly affected by factors such as the availability of the primary channel, imperfect spectrum sensing, and energy-constrained problems. Therefore, we propose a novel approach for wireless-powered cognitive radio networks (CRNs) to improve the transmission performance of secondary systems. To reduce the dependence of the secondary system on RF sources, in the paper, we provide a new paradigm by integrating ambient backscattering with both RF and non-RF wireless-powered communications to facilitate secondary communications. On the basis of the sensing result in a time slot, the secondary transmitter can dynamically select the operational action: (a) backscattering, (b) harvesting, or (c) transmitting to maximize the long-term achievable data transmission rate at the secondary receiver. In addition, the optimal action set for CRNs with wireless-powered ambient backscatter is selected by the partially observable Markov decision process (POMDP), which maximizes an expected transmission rate calculated over a number of subsequent time slots. The proposed scheme aims to improve long-term transmission rate of CRNs with wireless-powered ambient backscatter in comparison with conventional schemes where an action is taken only to maximize the immediate reward in every single time slot.
IEEE Sensors Journal, 2019
This paper studies an optimal transmit power decision policy for energy-efficient data transmissi... more This paper studies an optimal transmit power decision policy for energy-efficient data transmissions between a sensor node (i.e. the source) and a cluster head (i.e. the destination) in cluster-based wireless sensor networks in the presence of a full-duplex (FD) active eavesdropper. In this network, the source is powered by a wireless energy harvester, while the destination is constantly supplied by traditional electrical energy. The eavesdropper is capable of FD transmitting and receiving, and hence, opportunistically launches jamming attacks against the destination while eavesdropping, which affects not just the legitimate transmissions but the eavesdropper itself. The destination can also work in FD mode to simultaneously receive information signals and send an artificial noise to interfere with the eavesdropper. Therefore, we investigate an optimal power allocation policy for the source in order to maximize the secrecy transmission rate against an FD eavesdropper. In addition, we study the problem of decision making in two different scenarios. First, the legitimate nodes are assumed to have prior information about the arrival of harvested energy and about the eavesdropper's jamming attack model. The problem is formulated as the framework of a partially observable Markov decision process and is solved with value iteration-based dynamic programming. Secondly, the legitimate nodes do not know the dynamics of the environment in advance, so the problem becomes a standard Markov decision process. Hence, we propose an actor-critic learning framework to find the solution from practical interactions with the environment. Finally, we verify the performance of the proposed schemes by simulations.
IEEE Sensors Journal, 2018
In this paper, we investigate a security mode decision policy for a cognitive radio network (CRN)... more In this paper, we investigate a security mode decision policy for a cognitive radio network (CRN) powered by a nonradio frequency (RF) energy harvester. In such a network, a cognitive user (CU), which has a finite battery capacity, senses the presence of the primary user (PU) and tries to access the time-slotted primary channel opportunistically to transmit data. However, communication can be vulnerable to sudden attacks that are carried out by hidden eavesdroppers. Therefore, we propose an energy-efficient data encryption scheme for CRNs to increase the effective security level under energy limitation constraints. The operation mode decision policy is formulated as a framework of a partially observable Markov decision process (POMDP). In this approach, based on the sensing results and the remaining energy at the beginning of each time slot, CUs can decide to stay silent to save energy, or become active and encrypt data using opportune private-key encryption methods considering the effect of the current action on the future reward to maximize the effective security. Finally, we evaluate the performance of the proposed scheme by using numerical simulation results.
Wireless Networks, 2019
The cognitive radio network (CRN) is not only considered a useful medium for users, but it is als... more The cognitive radio network (CRN) is not only considered a useful medium for users, but it is also an environment vulnerable to proactive attackers. This paper studies an attack strategy for a legitimate energy-constrained eavesdropper (e.g., a government agency) to efficiently capture the suspicious wireless communications (i.e., an adversary communications link) in the physical layer of a CRN in tactical wireless networks. Since it is powered by an energy harvesting device, a full-duplex active eavesdropper constrained by a limited energy budget can simultaneously capture data and interfere with the suspicious cognitive transmissions to maximize the achievable wiretap rate while minimizing the suspicious transmission rate over a Rayleigh fading channel. The cognitive user operation is modeled in a time-slotted fashion. In this paper, we formulate the problem of maximizing a legitimate attack performance by adopting the framework of a partially observable Markov decision process. The decision is determined based on the remaining energy and a belief regarding the licensed channel activity in each time slot. Particularly, in each time slot, the eavesdropper can perform an optimal action based on two functional modes: (1) passive eavesdropping (overhearing data without jamming) or (2) active eavesdropping (overhearing data with the optimal amount of jamming energy) to maximize the long-term benefit. We illustrate the optimal policy and compare the performance of the proposed scheme with that of conventional schemes where the decision for the current time slot is only considered to maximize its immediate reward.
Sensors (Basel, Switzerland), Jan 15, 2018
The full-duplex transmission protocol has been widely investigated in the literature in order to ... more The full-duplex transmission protocol has been widely investigated in the literature in order to improve radio spectrum usage efficiency. Unfortunately, due to the effect of imperfect self-interference suppression, the change in transmission power and path loss of non-line-of-sight fading channels will strongly affect performance of full-duplex transmission mode. This entails that the full-duplex transmission protocol is not always a better selection compared to the traditional half-duplex transmission protocol. Considering solar energy-harvesting-powered cognitive radio networks (CRNs), we investigate a joint full-duplex/half-duplex transmission switching scheduling and transmission power allocation in which we utilize the advantages of both half-duplex and full-duplex transmission modes for maximizing the long-term throughput of cognitive radio networks. First, we formulate the transmission rate of half-duplex and full-duplex links for fading channels between cognitive user and ba...
IEEE Sensors Journal, 2017
Herein the authors consider harvested energy powered cognitive radio networks (CRNs) in which har... more Herein the authors consider harvested energy powered cognitive radio networks (CRNs) in which harvested energy is stored in a rechargeable battery which has finite capacity. In addition, a practical scenario in which the amount of harvested power is finite is taken into account. Cognitive users (CUs) opportunistically access a licensed channel (or primary channel); Meanwhile, it should be ensured that their confidential communications are not leaked to an eavesdropper. We investigate an optimal spectrum sensing schedule and the optimal amount of transmission energy for the CUs in each processing time slot. In particular, at the beginning of each time slot, based on the remaining energy in the battery, CU transmitter decides either (i) to be active to sense the channel and transmit its data if the channel is found vacant or (ii) to stay inactive during the current time slot in order to save energy and wait for more incoming energy for use in the next time slots. The decision is based on expected secrecy transmission rate calculated for both cases over subsequent K time slots. The proposed scheme aims to improve long-term secrecy transmission rate of CRNs in comparison with an conventional scheme where the decision for the current time slot is made to maximize current secrecy transmission rate without considering any future reward.
IEICE Transactions on Communications, 2017
IET Communications, 2016
An optimal multi-slot channel sensing schedule is proposed in this study that considers an opport... more An optimal multi-slot channel sensing schedule is proposed in this study that considers an opportunistic spectrum access with the awareness of channel switching delay and imperfect sensing. A practical case is considered where channel availability statistics are usually correlated in time slots and in frequency channels. The switching delays between channels, hardware constraints, and collision with other cognitive users are considered to find an optimal sensing order of the channels that maximises throughput of cognitive user. The optimal sensing order is obtained using the partially observable Markov decision process framework. Throughput of cognitive user, with and without channel sensing errors, is analytically derived and for each case an algorithm is developed. The proposed scheme mitigates the effect of channel sensing errors on the throughput. Performance of the proposed scheme is evaluated through simulations by comparing it with the existing schemes in the literature.
Sensors, 2016
This paper considers cognitive radio networks (CRNs) utilizing multiple time-slotted primary chan... more This paper considers cognitive radio networks (CRNs) utilizing multiple time-slotted primary channels in which cognitive users (CUs) are powered by energy harvesters. The CUs are under the consideration that hardware constraints on radio devices only allow them to sense and transmit on one channel at a time. For a scenario where the arrival of harvested energy packets and the battery capacity are finite, we propose a scheme to optimize (i) the channel-sensing schedule (consisting of finding the optimal action (silent or active) and sensing order of channels) and (ii) the optimal transmission energy set corresponding to the channels in the sensing order for the operation of the CU in order to maximize the expected throughput of the CRN over multiple time slots. Frequency-switching delay, energy-switching cost, correlation in spectrum occupancy across time and frequency and errors in spectrum sensing are also considered in this work. The performance of the proposed scheme is evaluated via simulation. The simulation results show that the throughput of the proposed scheme is greatly improved, in comparison to related schemes in the literature. The collision ratio on the primary channels is also investigated.
Proceedings of the 2019 2nd International Conference on Electronics, Communications and Control Engineering
Conventionally, to investigate the aging effects in analog-circuit-design phase, it requires to s... more Conventionally, to investigate the aging effects in analog-circuit-design phase, it requires to simulate, modify and verify iteratively on a number of circuit samples. In this work, we propose a fast aging simulation scheme for analog circuit modification and verification process based on the delta model in which the delta circuits are made from the delta devices built with the aging effect models by Verilog-A. During simulation, the aging device parameters are also updated continuously to attain the same accuracy with works in the literature; however, we only simulate the signal-difference between two similar circuits by re-using the previous simulation results to accelerate the aging simulation process. The experiment results show that, in the scenario of channel hot carrier effect on an analog amplifier circuit, the aging simulation process of the proposed scheme can be sped-up 10 times compared to that of conventional scheme with almost the same accuracy.
Proceedings of the 3rd International Conference on Electronics, Communications and Control Engineering
Herein, we propose a fast yield estimation approach for analog circuits design in which we combin... more Herein, we propose a fast yield estimation approach for analog circuits design in which we combine the behavioral model of circuit and the Quasi-Monte Carlo (QMC) sampling technique to accelerate yield estimation process. The behavioral model is constructed in Verilog-A based on the simulation results which are done at transistor-level; then, the accuracy of the model is verified by experimental testing on a specific analog circuit. Furthermore, instead of using random circuit samples, in this work, QMC circuit samples are adopted to obtain faster convergence rates for the yield prediction process. In conventional analog design stage, designers repeat a number of yield estimation process to select the optimal design point. Each yield estimation effort is a time-consuming process since designers have to simulate on a large number of circuits. Unlike the conventional method, in this work, we build a look-up table for constructing behavioral model of any given circuit; then, this table can be reused in repeating the yield-estimation processes. Therefore, the proposed method can significantly reduce the time for the yield estimation process. Experimental results show that the proposed approach can speed-up the yield estimation process 8 times compared to conventional simulation-based methods with a reasonable drop in accuracy (less than 5%).
Wireless Networks, 2021
Non-orthogonal multiple access (NOMA) is one of the promising techniques for spectrum efficiency ... more Non-orthogonal multiple access (NOMA) is one of the promising techniques for spectrum efficiency in wireless networks. In this paper, we consider an uplink NOMA cognitive system, where the secondary users (SUs) can jointly transmit data to the cognitive base station (CBS) over the same spectrum resources. Thereafter, successive interference cancellation is applied at the CBS to retrieve signals transmitted by the SUs. In addition, the energy-constrained problem in wireless networks is taken into account. Therefore, we assume that the SUs are powered by a wireless energy harvester to prolong their operations; meanwhile, the CBS is equipped with a traditional electrical supply. Herein, we propose an actor–critic reinforcement learning approach to maximize the long-term throughput of the cognitive network. In particular, by interacting and learning directly from the environment over several time slots, the CBS can optimally assign the amount of transmission energy for each SU according...
IEEE Access, 2021
The performance of data aggregation in industrial wireless communications can be degraded by envi... more The performance of data aggregation in industrial wireless communications can be degraded by environmental interference on Industrial Scientific Medical (ISM) channels. In this paper, the opportunistic spectrum access capability of cognitive radio (CR) was applied to enable devices to share primary channels with the aim of enhancing the transmission performance of the WirelessHART network. We considered a linear convergecast network, where the packets generated at each device were routed to the gateway (GW) through the aid of neighboring devices. The solar-powered cognitive access points (CAPs) were deployed to improve the successful transmission probability of the packets among field devices by opportunistically allocating the primary channels to the devices for data transmissions. In this paper, we formulate the scheduling problem of long-term throughput maximization as a framework of a Markov decision process by considering the constraints of the minimum delay, the number of required ISM channels, and the harvested energy at the CAPs. Then, we propose a deep reinforcement learning-based scheduling scheme to optimally assign multiple ISM and primary channels to the field devices in each superframe to maximize the received packets at the GW. The simulation results confirmed the superiority of the proposed scheme compared to existing methods. INDEX TERMS wirelessHART, cognitive radio, markov decision process, industrial scientific medical
Applied Sciences, 2020
Non-orthogonal multiple access (NOMA) is considered a potential technique in fifth-generation (5G... more Non-orthogonal multiple access (NOMA) is considered a potential technique in fifth-generation (5G). Nevertheless, it is relatively complex when applying NOMA to a massive access scenario. Thus, in this paper, a hybrid NOMA/OMA scheme is considered for uplink wireless transmission systems where multiple cognitive users (CUs) can simultaneously transmit their data to a cognitive base station (CBS). We adopt a user-pairing algorithm in which the CUs are grouped into multiple pairs, and each group is assigned to an orthogonal sub-channel such that each user in a pair applies NOMA to transmit data to the CBS without causing interference with other groups. Subsequently, the signal transmitted by the CUs of each NOMA group can be independently retrieved by using successive interference cancellation (SIC). The CUs are assumed to harvest solar energy to maintain operations. Moreover, joint power and bandwidth allocation is taken into account at the CBS to optimize energy and spectrum efficie...
IOP Conference Series: Materials Science and Engineering, 2021
In this paper, we present the design of a low-cost remote monitoring and control network for hous... more In this paper, we present the design of a low-cost remote monitoring and control network for household cultivation, in which peripherals connected to each sensor-node can be re-configured remotely from the internet via a master node without any changing on the system firmware. The feasibility of the proposed scheme is evaluated via experiments. Particularly, the experiments set-up consists of one master node communicating wirelessly with some sensor nodes (slaves) to collect sensing data or send commands to them to manage the operating of the system. The sensing data from slaves will be collected and updated periodically to Google Sheets by master node via the internet connection. Additionally, slaves are equipped with versatile ports for connecting with sensors. The port is designed to be compatible with most popular communication standards such as analog, digital, I2C, UART, SPI. The key design of these communication ports is that when plugging/unplugging a sensor into/from a port, the corresponding slave can be re-configured directly on Google Sheets or keypad connected to master node. The research results can be further extended and improved to be applicable to household cultivation as well as application models of smart agriculture.
Electronics, 2020
Currently, deploying fixed terrestrial infrastructures is not cost-effective in temporary circums... more Currently, deploying fixed terrestrial infrastructures is not cost-effective in temporary circumstances, such as natural disasters, hotspots, and so on. Thus, we consider a system of caching-based UAV-assisted communications between multiple ground users (GUs) and a local station (LS). Specifically, a UAV is exploited to cache data from the LS and then serve GUs’ requests to handle the issue of unavailable or damaged links from the LS to the GUs. The UAV can harvest solar energy for its operation. We investigate joint cache scheduling and power allocation schemes by using the non-orthogonal multiple access (NOMA) technique to maximize the long-term downlink rate. Two scenarios for the network are taken into account. In the first, the harvested energy distribution of the GUs is assumed to be known, and we propose a partially observable Markov decision process framework such that the UAV can allocate optimal transmission power for each GU based on proper content caching over each flig...
IEEE Sensors Journal, 2019
Physical layer wireless communications are more and more essential, and are vulnerable to malicio... more Physical layer wireless communications are more and more essential, and are vulnerable to malicious users owing to the nature of broadcast channels. Herein, we consider a centralized multi-channel cognitive radio network in the presence of eavesdroppers (EVEs). In the network, the secondary base station (SBS) shares currently free primary channels to simultaneously communicate with secondary users (SUs), while passive eavesdroppers attempt to overhear data in the secondary communications. Each limited-battery SU is equipped with two antennas (one for transmitting signals, and other for receiving signals) and is powered by a solar energy harvester. Meanwhile, the SBS equipped with multiple antennas can operate in full-duplex (FD) transmission mode (simultaneously transmit and receive signals) or in half-duplex (HD) transmission mode (transmit and receive signals in turn during each half of a time slot) with the SUs. In this paper, we propose a novel scheme to maximize the secondary system security of the multi-channel cognitive system in the presence of multiple passive EVEs, in which the EVEs are able to overhear the data of the SBS−SU transmissions on all the primary channels. The problem of decision making is formulated as the framework of a partially observable Markov decision process (POMDP), and an optimal solution is achieved by adopting value iteration−based dynamic programming. Specifically, in each time slot, the SBS allocates optimal channel and optimal action (i.e. either stay silent or employ HD/FD transmission modes with optimal transmission power) for each SU in order to obtain maximum long-term secrecy rate for the secondary system.
International Journal of Communication Systems, 2019
Wireless energy harvesting enables wireless-powered communications to accommodate data services i... more Wireless energy harvesting enables wireless-powered communications to accommodate data services in a self-sustainable manner over a long operational time. Along with energy harvesting, an ambient backscatter technique helps a secondary transmitter reflect existing radio frequency (RF) signal sources to communicate with a secondary receiver when the primary channel (PC) is utilized. However, secondary system performance is significantly affected by factors such as the availability of the primary channel, imperfect spectrum sensing, and energy-constrained problems. Therefore, we propose a novel approach for wireless-powered cognitive radio networks (CRNs) to improve the transmission performance of secondary systems. To reduce the dependence of the secondary system on RF sources, in the paper, we provide a new paradigm by integrating ambient backscattering with both RF and non-RF wireless-powered communications to facilitate secondary communications. On the basis of the sensing result in a time slot, the secondary transmitter can dynamically select the operational action: (a) backscattering, (b) harvesting, or (c) transmitting to maximize the long-term achievable data transmission rate at the secondary receiver. In addition, the optimal action set for CRNs with wireless-powered ambient backscatter is selected by the partially observable Markov decision process (POMDP), which maximizes an expected transmission rate calculated over a number of subsequent time slots. The proposed scheme aims to improve long-term transmission rate of CRNs with wireless-powered ambient backscatter in comparison with conventional schemes where an action is taken only to maximize the immediate reward in every single time slot.
IEEE Sensors Journal, 2019
This paper studies an optimal transmit power decision policy for energy-efficient data transmissi... more This paper studies an optimal transmit power decision policy for energy-efficient data transmissions between a sensor node (i.e. the source) and a cluster head (i.e. the destination) in cluster-based wireless sensor networks in the presence of a full-duplex (FD) active eavesdropper. In this network, the source is powered by a wireless energy harvester, while the destination is constantly supplied by traditional electrical energy. The eavesdropper is capable of FD transmitting and receiving, and hence, opportunistically launches jamming attacks against the destination while eavesdropping, which affects not just the legitimate transmissions but the eavesdropper itself. The destination can also work in FD mode to simultaneously receive information signals and send an artificial noise to interfere with the eavesdropper. Therefore, we investigate an optimal power allocation policy for the source in order to maximize the secrecy transmission rate against an FD eavesdropper. In addition, we study the problem of decision making in two different scenarios. First, the legitimate nodes are assumed to have prior information about the arrival of harvested energy and about the eavesdropper's jamming attack model. The problem is formulated as the framework of a partially observable Markov decision process and is solved with value iteration-based dynamic programming. Secondly, the legitimate nodes do not know the dynamics of the environment in advance, so the problem becomes a standard Markov decision process. Hence, we propose an actor-critic learning framework to find the solution from practical interactions with the environment. Finally, we verify the performance of the proposed schemes by simulations.
IEEE Sensors Journal, 2018
In this paper, we investigate a security mode decision policy for a cognitive radio network (CRN)... more In this paper, we investigate a security mode decision policy for a cognitive radio network (CRN) powered by a nonradio frequency (RF) energy harvester. In such a network, a cognitive user (CU), which has a finite battery capacity, senses the presence of the primary user (PU) and tries to access the time-slotted primary channel opportunistically to transmit data. However, communication can be vulnerable to sudden attacks that are carried out by hidden eavesdroppers. Therefore, we propose an energy-efficient data encryption scheme for CRNs to increase the effective security level under energy limitation constraints. The operation mode decision policy is formulated as a framework of a partially observable Markov decision process (POMDP). In this approach, based on the sensing results and the remaining energy at the beginning of each time slot, CUs can decide to stay silent to save energy, or become active and encrypt data using opportune private-key encryption methods considering the effect of the current action on the future reward to maximize the effective security. Finally, we evaluate the performance of the proposed scheme by using numerical simulation results.
Wireless Networks, 2019
The cognitive radio network (CRN) is not only considered a useful medium for users, but it is als... more The cognitive radio network (CRN) is not only considered a useful medium for users, but it is also an environment vulnerable to proactive attackers. This paper studies an attack strategy for a legitimate energy-constrained eavesdropper (e.g., a government agency) to efficiently capture the suspicious wireless communications (i.e., an adversary communications link) in the physical layer of a CRN in tactical wireless networks. Since it is powered by an energy harvesting device, a full-duplex active eavesdropper constrained by a limited energy budget can simultaneously capture data and interfere with the suspicious cognitive transmissions to maximize the achievable wiretap rate while minimizing the suspicious transmission rate over a Rayleigh fading channel. The cognitive user operation is modeled in a time-slotted fashion. In this paper, we formulate the problem of maximizing a legitimate attack performance by adopting the framework of a partially observable Markov decision process. The decision is determined based on the remaining energy and a belief regarding the licensed channel activity in each time slot. Particularly, in each time slot, the eavesdropper can perform an optimal action based on two functional modes: (1) passive eavesdropping (overhearing data without jamming) or (2) active eavesdropping (overhearing data with the optimal amount of jamming energy) to maximize the long-term benefit. We illustrate the optimal policy and compare the performance of the proposed scheme with that of conventional schemes where the decision for the current time slot is only considered to maximize its immediate reward.
Sensors (Basel, Switzerland), Jan 15, 2018
The full-duplex transmission protocol has been widely investigated in the literature in order to ... more The full-duplex transmission protocol has been widely investigated in the literature in order to improve radio spectrum usage efficiency. Unfortunately, due to the effect of imperfect self-interference suppression, the change in transmission power and path loss of non-line-of-sight fading channels will strongly affect performance of full-duplex transmission mode. This entails that the full-duplex transmission protocol is not always a better selection compared to the traditional half-duplex transmission protocol. Considering solar energy-harvesting-powered cognitive radio networks (CRNs), we investigate a joint full-duplex/half-duplex transmission switching scheduling and transmission power allocation in which we utilize the advantages of both half-duplex and full-duplex transmission modes for maximizing the long-term throughput of cognitive radio networks. First, we formulate the transmission rate of half-duplex and full-duplex links for fading channels between cognitive user and ba...
IEEE Sensors Journal, 2017
Herein the authors consider harvested energy powered cognitive radio networks (CRNs) in which har... more Herein the authors consider harvested energy powered cognitive radio networks (CRNs) in which harvested energy is stored in a rechargeable battery which has finite capacity. In addition, a practical scenario in which the amount of harvested power is finite is taken into account. Cognitive users (CUs) opportunistically access a licensed channel (or primary channel); Meanwhile, it should be ensured that their confidential communications are not leaked to an eavesdropper. We investigate an optimal spectrum sensing schedule and the optimal amount of transmission energy for the CUs in each processing time slot. In particular, at the beginning of each time slot, based on the remaining energy in the battery, CU transmitter decides either (i) to be active to sense the channel and transmit its data if the channel is found vacant or (ii) to stay inactive during the current time slot in order to save energy and wait for more incoming energy for use in the next time slots. The decision is based on expected secrecy transmission rate calculated for both cases over subsequent K time slots. The proposed scheme aims to improve long-term secrecy transmission rate of CRNs in comparison with an conventional scheme where the decision for the current time slot is made to maximize current secrecy transmission rate without considering any future reward.
IEICE Transactions on Communications, 2017
IET Communications, 2016
An optimal multi-slot channel sensing schedule is proposed in this study that considers an opport... more An optimal multi-slot channel sensing schedule is proposed in this study that considers an opportunistic spectrum access with the awareness of channel switching delay and imperfect sensing. A practical case is considered where channel availability statistics are usually correlated in time slots and in frequency channels. The switching delays between channels, hardware constraints, and collision with other cognitive users are considered to find an optimal sensing order of the channels that maximises throughput of cognitive user. The optimal sensing order is obtained using the partially observable Markov decision process framework. Throughput of cognitive user, with and without channel sensing errors, is analytically derived and for each case an algorithm is developed. The proposed scheme mitigates the effect of channel sensing errors on the throughput. Performance of the proposed scheme is evaluated through simulations by comparing it with the existing schemes in the literature.
Sensors, 2016
This paper considers cognitive radio networks (CRNs) utilizing multiple time-slotted primary chan... more This paper considers cognitive radio networks (CRNs) utilizing multiple time-slotted primary channels in which cognitive users (CUs) are powered by energy harvesters. The CUs are under the consideration that hardware constraints on radio devices only allow them to sense and transmit on one channel at a time. For a scenario where the arrival of harvested energy packets and the battery capacity are finite, we propose a scheme to optimize (i) the channel-sensing schedule (consisting of finding the optimal action (silent or active) and sensing order of channels) and (ii) the optimal transmission energy set corresponding to the channels in the sensing order for the operation of the CU in order to maximize the expected throughput of the CRN over multiple time slots. Frequency-switching delay, energy-switching cost, correlation in spectrum occupancy across time and frequency and errors in spectrum sensing are also considered in this work. The performance of the proposed scheme is evaluated via simulation. The simulation results show that the throughput of the proposed scheme is greatly improved, in comparison to related schemes in the literature. The collision ratio on the primary channels is also investigated.