• 한국정보통신설비학회:학술대회논문집
• /
• 2007.08a
• /
• pp.46-49
• /
• 2007

Multiple Antenna Technologies such as Multiple-Input Multiple-Output (MIMO) and Beamforming provide the increase of channel capacity and the reliability of wireless link. To obtain these advantages, WiBro, Mobile WiMAX and $4^{th}$ Generation System are employing multiple antenna technologies. There exist, however, many technical issues in considering the application of the technologies or the providing of services using them. In this paper, various technical topics are discussed and simple solutions are proposed. Beamforming has several technical issues which include coverage imbalance, difficulties in providing Multicast-Broadcast Service (MBS). In Addition, network planning is a critical point from a cell extension and initial network entry point of view. In case of MIMO, network deployment is discussed in that cellular data network such as WiBro has many repeaters. MIMO mode selection for maximizing the cell capacity is also covered.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.8
• /
• pp.3789-3808
• /
• 2017

This paper studies a multi-antenna wireless relay network in the presence of a jammer. In this network, the source node transmits signals to the destination node through a multi-antenna relay node which adopts the amplify-and-forward scheme, and the jammer attempts to inject additive signals on all antennas of the relay node. With the linear beamforming scheme at the relay node, this network can be modeled as an equivalent Gaussian arbitrarily varying channel (GAVC). Based on this observation, we deduce the mathematical closed-forms of the capacities for two special cases and the suboptimal achievable rate for the general case, respectively. To reduce complexity, we further propose an optimal structure of the beamforming matrix. In addition, we present a second order cone programming (SOCP)-based algorithm to efficiently compute the optimal beamforming matrix so as to maximize the transmission rate between the source and the destination when the perfect channel state information (CSI) is available. Our numerical simulations show significant improvements of our propose scheme over other baseline ones.

• Journal of Communications and Networks
• /
• v.14 no.6
• /
• pp.619-628
• /
• 2012

The ZigBee network has been considered to monitor electricity usage of home appliances in the smart grid network. ZigBee, however, may suffer from a coexistence problem with wireless local area network (WLAN). In this paper, to resolve the coexistence problem between ZigBee network and WLAN, we propose a new protocol constructing a cognitive smart grid network for supporting monitoring of home appliances. In the proposed protocol, home appliances first estimates the transmission timing and channel information of WLAN by reading request to send/clear to send (RTS/CTS) frames of WLAN. Next, based on the estimated information, home appliances transmit a data at the same time as WLAN transmission. To manage the interference between WLAN and smart grid network, we propose a cognitive beamforming algorithm. The beamforming algorithm is designed to guaranteeing zero interference to WLAN while satisfying a required rate for smart metering. We also propose an energy efficient rate adaptation algorithm. By slowing down the transmission rate while satisfying an imperceptible impact of quality of service (QoS) of the receiver, the home appliance can significantly save transmit power. Numerical results show that the proposed multiple antenna technique provides reliable communications for smart metering with reduced power comparing to the simple transmission technique.

• International journal of advanced smart convergence
• /
• v.9 no.2
• /
• pp.58-67
• /
• 2020

In this paper, we propose a data-driven-based beam selection scheme for massive multiple-input and multiple-output (MIMO) systems in ultra-dense networks (UDN), which is capable of addressing the problem of high computational cost of conventional coordinated beamforming approaches. We consider highly dense small-cell scenarios with more small cells than mobile stations, in the millimetre-wave band. The analog beam selection for hybrid beamforming is a key issue in realizing millimetre-wave UDN MIMO systems. To reduce the computation complexity for the analog beam selection, in this paper, two deep neural network models are used. The channel samples, channel gains, and radio frequency beamforming vectors between the access points and mobile stations are collected at the central/cloud unit that is connected to all the small-cell access points, and are used to train the networks. The proposed machine-learning-based scheme provides an approach for the effective implementation of massive MIMO system in UDN environment.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.1
• /
• pp.16-22
• /
• 2015

This paper proposes a power allocation method for multiple node beamforming with uniform circular array antennas to increase SIR of nodes in wireless mesh network. The proposed method calculates beamforming power allocation vectors that maximizes SIR satisfied with power constraint of HPA. The simulation results demonstrate the proposed method achieves the enhanced SIR of nodes than that of beamforming method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.6
• /
• pp.1379-1397
• /
• 2013

We consider a system where a licensed radio spectrum is shared by multiple primary users(PUs) and secondary users(SUs). As the spectrum of interest is licensed to primary network, power and channel allocation must be carried out within the cognitive radio network so that no excessive interference is caused to PUs. For this system, we study the joint beamforming and power allocation problem via game theory in this paper. The problem is formulated as a non-cooperative beamforming and power allocation game, subject to the interference constraints of PUs as well as the peak transmission power constraints of SUs. We design a joint beamforming and power allocation algorithm for maximizing the total throughput of SUs, which is implemented by alternating iteration of minimum mean square error based decision feedback beamforming and a best response based iterative power allocation algorithm. Simulation results show that the algorithm has better performance than an existing algorithm and can converge to a locally optimal sum utility.

• ETRI Journal
• /
• v.43 no.2
• /
• pp.221-231
• /
• 2021

To resolve energy depletion issues in massive Internet of Things sensor networks, we developed a set of distributed energy beamforming methods with one-bit feedback and clustering for multi-node wireless energy transfer, where multiple singleantenna distributed energy transmitters (Txs) transfer their energy to multiple nodes wirelessly. Unlike previous works focusing on distributed information beamforming using a single energy receiver (Rx) node, we developed a distributed energy beamforming method for multiple Rx nodes. Additionally, we propose two clustering methods in which each Tx node chooses a suitable Rx node. Furthermore, we propose a fast distributed beamforming method based on Tx sub-clustering. Through computer simulations, we demonstrate that the proposed distributed beamforming method makes it possible to transfer wireless energy to massive numbers of sensors effectively and rapidly with small implementation complexity. We also analyze the energy harvesting outage probability of the proposed beamforming method, which provides insights into the design of wireless energy transfer networks with distributed beamforming.

• ETRI Journal
• /
• v.36 no.4
• /
• pp.625-634
• /
• 2014

This paper studies a dual-hop multiple-access relay network where two independent source nodes transmit information to a common destination node with the aid of multiple single-antenna amplify-and-forward relays. Each relay node is subject to an individual power constraint. We focus on the design of distributed beamforming schemes for the relays to support the transmission rate requirements of the two sources. To this end, we first characterize the achievable rate region for this network via solving a sequence of corner point optimization problems proposed in this paper. We also develop several low-complexity suboptimal schemes in closed form. Two inner bounds of the achievable rate region are theoretically shown to be approximately optimal in two special scenarios. Finally, numerical results demonstrate the effectiveness of our proposed approaches.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.9
• /
• pp.1686-1692
• /
• 2015

This paper proposes a modified genetic algorithm that has the same beamforming performance and a fast convergence speed using general genetic algorithm in order to form a beam for the mobile node in a mesh network. The proposed beamforming genetic algorithm selects a part of chromosome a high fitness value in mating process to obtain fast convergence speed, and rest part of chromosome with longer fitness value in order to avoid local solution. Furthermore, the reference beam pattern with Gaussian shape reduces additional convergence speed. Simulation shows that the convergence speed of proposed algorithm improves 20% compared with that of conventional beamforming genetic algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.1
• /
• pp.1-19
• /
• 2020

In an underlay cognitive simultaneous wireless information and power transfer (SWIPT) network, communication from secondary user (SU) to secondary destination (SD) is accomplished with decode-and-forward (DF) relays. Multiple energy-constrained relays are assumed to harvest energy from SU via power splitting (PS) protocol and complete SU secure information transmission with beamforming. Hence, physical layer security (PLS) is investigated in cognitive SWIPT network. In order to interfere with eavesdropper and improve relay's energy efficiency, a destination-assisted jamming scheme is proposed. Namely, SD transmits artificial noise (AN) to interfere with eavesdropping, while jamming signal can also provide harvested energy to relays. Beamforming vector and power splitting ratio are jointly optimized with the objective of SU secrecy capacity maximization. We solve this non-convex optimization problem via a general two-stage procedure. Firstly, we obtain the optimal beamforming vector through semi-definite relaxation (SDR) method with a fixed power splitting ratio. Secondly, the best power splitting ratio can be obtained by one-dimensional search. We provide simulation results to verify the proposed solution. Simulation results show that the scheme achieves the maximum SD secrecy rate with appropriate selection of power splitting ratio, and the proposed scheme guarantees security in cognitive SWIPT networks.