• Journal of Communications and Networks
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• v.18 no.3
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• pp.320-326
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• 2016

In existing literature on multiple-input multiple-output (MIMO) relaying communication systems, antenna selection is often implemented by maximizing the channel capacity or the output single-to-noise ratio (SNR). In this paper, we propose an energy-efficient low-complexity antenna selection scheme for MIMO relaying communication systems. The proposed algorithm is based on beamforming and maximizing the Frobenius norm to jointly optimize the transmit power, number of active antennas, and antenna subsets at the source, relaying and destination. We maximize the energy efficiency between the link of source to relay and the link of relay to destination to obtain the maximum energy efficiency of the system, subject to the SNR constraint. Compared to existing antenna selection methods forMIMO relaying communication systems, simulation results demonstrate that the proposed method can save more power in term of energy efficiency, while having lower computational complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1790-1806
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• 2015

Utility-based routing is a special type of routing approach using a composite utility metric when making routing decisions in ad hoc and sensor networks. Previous studies on the utility-based routing all use fixed retry limit and a very simple distance related energy model, which makes the utility maximization less efficient and the implementation separated from practice. In this paper, we refine the basic utility model by capturing the correlation of the transmit power, the retry limit, the link reliability and the energy cost. A routing algorithm based on the refined utility model with adaptive transmit power and retry limit allocation is proposed. With this algorithm, packets with different priorities will automatically receive utility-optimal delivery. The design of this algorithm is based on the observation that for a given benefit, there exists a utility-maximum route with optimal transmit power and retry limit allocated to intermediate forwarding nodes. Delivery along the utility-optimal route makes a good balance between the energy cost and the reliability according to the value of the packets. Both centralized algorithm and distributed implementations are discussed. Simulations prove the satisfying performance of the proposed algorithm.

• Journal of Satellite, Information and Communications
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• v.11 no.2
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• pp.55-59
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• 2016

Conventional RF energy harvesting systems can harvest energy and decode information from same source as an Hybirid-AP (H-AP). However, harvesting efficiency is seriously dependent on distance between users and H-AP. Therefore, in this paper, we proposed a transmission model for RF harvesting consisting of information and power source separately called Decoupled RF Energy harvesting networks. Main purpose of this paper is to maximize energy efficiency under various constraints of transmit power from H-AP and power beacon (PB), minimum quality of service and quality of harvested power of each users. To measure proposed model's performance, we proposed optimal time scheduling algorithms for energy efficiency (EE) maximization using Lagrangian dual decomposition theory that locally maximizes the EE by obtaining suboptimal values of three arguments : transmit power of H-AP, transmit power of PB, frame splitting factor. Experiment results show that the proposed energy-efficient algorithms converge within a few iterations with its optimality and greatly improve the EE compared to that of baseline schemes.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.3-9
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• 2015

Under the maximum transmit power constraint and the minimum rate constraint, we propose the optimal number of transmit antennas and transmit power which maximize energy-efficiency (EE) in multi-user multiple-input multiple-output (MIMO) downlink system with the maximal ratio transmission (MRT) precoding. Because the optimization problem for the instantaneous channel is difficult to solve, we use independence of individual channel, average channel gain and path loss to approximate the objective function. Since the approximated EE optimization problem is two-dimensional search problem, we find the optimal number of transmit antennas and transmit power using Lagrange multipliers and our proposed algorithm. Simulation results show that the number of transmit antennas and power obtained by proposed algorithm are almost identical to the value by the exhaustive search.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.340-350
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• 2016

The performance of large-scale cognitive radio (CR) networks with secondary users sustained by opportunistically harvesting radio-frequency (RF) energy from nearby primary transmissions is investigated. Using an advanced RF energy harvester, a secondary user is assumed to be able to collect ambient primary RF energy as long as it lies inside the harvesting zone of an active primary transmitter (PT). A variable power (VP) transmission mode is proposed, and an energy-based opportunistic spectrum access (OSA) strategy is considered, under which a secondary transmitter (ST) is allowed to transmit only if its harvested energy is larger than a predefined transmission threshold and it is outside the guard zones of all active PTs. The transmission probability of the STs is derived. The outage probabilities and the throughputs of the primary and the secondary networks, respectively, are characterized. Compared with prior work, the throughput can be increased by as much as 29%. The energy-based OSA strategy can be generally applied to a non-CR setup, where distributed power beacons (PBs) are deployed to power coexisting wireless signal transmitters (WSTs) in a wireless powered sensor network.

• Journal of the Korea Society of Computer and Information
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• v.22 no.8
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• pp.41-46
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• 2017

In this paper, we investigate the D2D Transmitter(Tx) and Receiver(Rx) pair assignment problem in the cellular system where D2D users share the uplink resource of the cellular system. Sharing the uplink resource of the cellular system may cause interference to the cellular system, though it is beneficial to improve the D2D user Capacity. Therefore, to protect the cellular users, D2D transmit power should be carefully controlled. In this work, we focus on optimal Tx-Rx assignment in such a way that the total transmit power of users is minimized. First, we consider the optimum Tx-Rx assignment in general and the corresponding complexity. Then, we propose an iterative D2D Tx-Rx assignment algorithm with low complexity that can minimize total transmit power of users. Finally, we present the numerical examples that show the complexity and the convergence to the unique transmit power level.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.260-279
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• 2015

In this paper, we investigate physical layer security for multiple decode-and-forward (DF) relaying underlay cognitive radio networks (CRNs) with fixed transmit power at the secondary network against passive eavesdropping attacks. We propose a simple relay selection scheme to improve wireless transmission security based on the instantaneous channel information of all legitimate users and the statistical information about the eavesdropper channels. The closed-form expressions of the probability of non-zero secrecy capacity and the secrecy outage probability (SOP) are derived over independent and non-identically distributed Rayleigh fading environments. Furthermore, we conduct the asymptotic analysis to evaluate the secrecy diversity order performance and prove that full diversity is achieved by using the proposed relay selection. Finally, numerical results are presented to verify the theoretical analysis and depict that primary interference constrain has a significant impact on the secure performance and a proper transmit power for the second transmitters is preferred to be energy-efficient and improve the secure performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1249-1254
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• 2016

Recently, there have been many researches which can achieve high data rate in multi-user massive MIMO networks while reducing the complexity in terms of both hardware and algorithm. In addition, many researches have been conduced to reduce the energy consumption in next generation mobile communication networks. In this paper, we thus investigated new transmit antenna selection scheme to achieve low computational complexity and enhance energy efficiency in multi-user massive MIMO networks. First, we introduced the optimal scheme based on Brute-Force searching to maximize the energy efficiency and then proposed new antenna selection scheme to dramatically reduce the computational complexity compared to the optimal scheme. As the number of transmit antennas increases, the complexity of the optimal scheme exponentially increases while the complexity of the proposed scheme linearly increases. Nevertheless, the energy efficiency performance gap between proposed and optimal schemes is not huge.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1900-1911
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• 2015

In this paper, we introduce backscatter communication for power-limited sensors to enable long-range transmission in wireless sensor networks, and envision a way to avoid doubly near-far problem in wireless-powered communication network (WPCN) with this technology. In backscatter based WPCN, users harvest energy from both the signal broadcasted by the hybrid access point and the carrier signal transmitted by the carrier emitter in the downlink, and then transmit their own information in a passive way via the reflection of the carrier signal using frequency-shift keying modulation in the uplink. We characterize the energy-free condition and the signal-to-noise ratio (SNR) outage zone in backscatter based WPCN. Further, we propose backscatter based harvest-then-transmit protocol to maximize the sum-throughput of the backscatter based WPCN by optimally allocating time for energy harvesting and information transmission. Numerical results demonstrate that the backscatter based WPCN increases significantly the transmission range and diminishes greatly the SNR outage zone.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3172-3193
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• 2022

Cognitive radio-simultaneous wireless information and power transfer (CR-SWIPT) has attracted much interest since it can improve both the spectrum and energy efficiency of wireless networks. This paper focuses on the resource sharing between a point-to-point primary system (PRS) and a multiuser multi-antenna cellular cognitive radio system (CRS) containing a large number of cognitive users (CUs). The resource sharing optimization problem is formulated by jointly scheduling CUs and adjusting the transmit power at the cognitive base station (CBS). The effect of accessing CUs' spatial channel correlation on the possible transmit power of the CBS is investigated. Accordingly, we provide a low-complexity suboptimal approach termed the semi-correlated semi-orthogonal user selection (SC-SOUS) algorithm to enhance the spectrum efficiency. In the proposed algorithm, CUs that are highly correlated to the information decoding primary receiver (IPR) and mutually near orthogonal are selected for simultaneous transmission to reduce the interference to the IPR and increase the sum rate of the CRS. We further develop a spatial correlation-based resource sharing (SC-RS) strategy to improve energy sharing performance. CUs nearly orthogonal to the energy harvesting primary receiver (EPR) are chosen as candidates for user selection. Therefore, the EPR can harvest more energy from the CBS so that the energy utilization of the network can improve. Besides, zero-forcing precoding and power control are adopted to eliminate interference within the CRS and meet the transmit power constraints. Simulation results and analysis show that, compared with the existing CU selection methods, the proposed low-complex strategy can enhance both the achievable sum rate of the CRS and the energy sharing capability of the network.