• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3907-3923
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• 2020

An enhanced irregular repetition slotted ALOHA (IRSA) protocol is proposed by using polarization characteristic of satellite link and MIMO detection in low earth orbit (LEO) satellite networks, which is dubbed polarized MIMO IRSA (PM-IRSA). In the proposed scheme, one or two packets in one slot can be decoded by employing polarized MIMO detection, and more than two collided packets in multiple slots which can construct the virtual MIMO model can be decoded by the MIMO detection algorithm. The performance of the proposed scheme is analyzed with the density evolution (DE) approach and the degree distribution is optimized to maximize the system throughput by using a differential evolution. Numerical results certify our analysis and show that the normalized throughput of the proposed PM-IRSA can achieve 1.89 bits/symbol.

• Journal of Communications and Networks
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• 제6권4호
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• pp.317-330
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• 2004

In this paper, we explore the utility of recently discovered multiple-antenna techniques (namely MIMO techniques) for medium access control (MAC) design and routing in mobile ad hoc networks. Specifically, we focus on ad hoc networks where the spatial diversity technique is used to combat fading and achieve robustness in the presence of user mobility. We first examine the impact of spatial diversity on the MAC design, and devise a MIMO MAC protocol accordingly. We then develop analytical methods to characterize the corresponding saturation throughput for MIMO multi-hop networks. Building on the throughout analysis, we study the impact of MIMO MAC on routing. We characterize the optimal hop distance that minimizes the end-to-end delay in a large network. For completeness, we also study MAC design using directional antennas for the case where the channel has a strong line of sight (LOS) component. Our results show that the spatial diversity technique and the directional antenna technique can enhance the performance of mobile ad hoc networks significantly.

• 한국정보통신학회논문지
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• 제20권7호
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• pp.1249-1254
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• 2016

최근 들어서, Multi-User Massive MIMO 네트워크에서 하드웨어와 알고리즘 측면에서 복잡도를 낮추면서 높은 전송률을 얻을 수 있는 다양한 전송 안테나 선택 기법에 대한 연구가 활발히 진행되고 있다. 또한, 차세대 이동통신 네트워크에서 에너지 소모량을 줄이기 위한 다양한 기술들에 대한 연구가 이루어지고 있다. 그래서, 본 논문에서는 Multi-User Massive MIMO 네트워크에서 낮은 계산 복잡도를 달성하면서 에너지 효율성을 높일 수 있는 전송 안테나 선택 기법을 연구하였다. 먼저, Brute-Force 탐색 기반의 최적 방식을 소개하고 최적 방식 대비 계산 복잡도를 획기적으로 줄일 수 있는 새로운 안테나 선택 기법을 제안하였다. 안테나 수가 증가할수록 최적 방식의 복잡도는 지수적으로 증가하는 반면 제안 방식은 선형적으로 증가한다. 그럼에도 불구하고, 제안 방식과 모든 경우를 고려하는 최적 방식의 에너지 효율 성능 차이는 크지 않다.

• Journal of Communications and Networks
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• 제12권3호
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• pp.231-239
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• 2010

In cluster-based wireless sensor networks, the energy could be saved when the nodes that have data to transmit participate in cooperative multiple-input multiple-output (MIMO). In this paper, by making the idle nodes that have no data to transmit participate in the cooperative MIMO, it is found that much more energy could be saved. The number of the idle nodes that participate in the cooperative MIMO is optimized to minimize the total energy consumption. It is also found that the optimal number of all the nodes participating in cooperative communication does not vary with the number of nodes that have data to transmit. The proposition is proved mathematically. The influence of long-haul distance and modulation constellation size on the total energy consumption is investigated. A cooperative MIMO scheme with help-node participation is proposed and the simulation results show that the proposed scheme achieves significant energy saving.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4242-4263
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• 2017

Multi-User Multiple-Input Multiple-Output (MU-MIMO) technology has recently attracted significant attention from academia and industry because of it is increasingly important role in improving networks' capacity and data rate. Moreover, MU-MIMO systems for the Fifth Generation (5G) have already been researched. High Quality of Service (QoS) and efficient operations at the Medium Access Control (MAC) layer have become key requirements. In this paper, we propose a downlink MU-MIMO MAC protocol based on adaptive Channel State Information (CSI) feedback (called MMM-A) for Wireless Local Area Networks (WLANs). A modified CSMA/CA mechanism using new frame formats is adopted in the proposed protocol. Specifically, the CSI is exchanged between stations (STAs) in an adaptive way, and a packet selection strategy which can guarantee a fairer QoS for scenarios with differentiated traffic is also included in the MMM-A protocol. We then derive the expressions of the throughput and access delay, and analyze the performance of the protocol. It is easy to find that the MMM-A protocol outperforms the commonly used protocols in terms of the saturated throughput and access delay through simulation and analysis results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4738-4758
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• 2017

Resource allocation plays a crucial role in multiuser multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems to improve overall system performance. While previously proposed resource allocation algorithms are mainly designed from the point of view of the information-theoretic, we formulate the resource allocation problem as an average bit error rate (BER) minimization problem subject to a total power constraint when considering employing realistic MIMO detection techniques. Subsequently, we derive the optimal subcarrier and power allocation algorithms for three types of well-known MIMO detectors, including the maximum likelihood (ML) detector, linear detectors, and successive interference cancellation (SIC) detectors. To reduce the complexity, we also propose a two-step suboptimal algorithm that separates subcarrier and power allocation for each detector. We also analyze the diversity gain of the proposed suboptimal algorithms for various MIMO detectors. Simulation results confirm that the proposed suboptimal algorithm for each detector can achieve a comparable performance with the optimal allocation with a much lower complexity. Moreover, it is shown that the suboptimal algorithms perform better than the conventional algorithms that are known in the literature.

• ETRI Journal
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• 제42권3호
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• pp.341-350
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• 2020

In a wireless sensor network (WSN), the data transmission technique based on the cooperative multiple-input multiple-output (CMIMO) scheme reduces the energy consumption of sensor nodes quite effectively by utilizing the space-time block coding scheme. However, in networks with high node density, the scheme is ineffective due to the high degree of correlated data. Therefore, to enhance the energy efficiency in high node density WSNs, we implemented the distributed source coding (DSC) with the virtual multiple-input multiple-output (MIMO) data transmission technique in the WSNs. The DSC-MIMO first compresses redundant source data using the DSC and then sends it to a virtual MIMO link. The results reveal that, in the DSC-MIMO scheme, energy consumption is lower than that in the CMIMO technique; it is also lower in the DSC single-input single-output (SISO) scheme, compared to that in the SISO technique at various code rates, compression rates, and training overhead factors. The results also indicate that the energy consumption per bit is directly proportional to the velocity and training overhead factor in all the energy saving schemes.

• Journal of Communications and Networks
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• 제7권3호
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• pp.284-293
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• 2005

A critical issue in applications involving networks of wireless sensors is their ability to synchronize, and mitigate the fading propagation channel effects. Especially when distributed 'slave' sensors (nodes) reach-back to communicate with the 'master' sensor (gateway), low power cooperative schemes are well motivated. Viewing each node as an antenna element in a multi-input multi-output (MIMO) multi-antenna system, we design pilot patterns to estimate the multiple carrier frequency offsets (CFO), and the multiple channels corresponding to each node-gateway link. Our novel pilot scheme consists of non-zero pilot symbols along with zeros, which separate nodes in a time division multiple access (TDMA) fashion, and lead to low complexity schemes because CFO and channel estimators per node are decoupled. The resulting training algorithm is not only suitable for wireless sensor networks, but also for synchronization and channel estimation of single- and multi-carrier MIMO systems. We investigate the performance of our estimators analytically, and with simulations.

• Journal of Multimedia Information System
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• 제3권4호
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• pp.141-148
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• 2016

This paper proposes a medium access control (MAC) protocol for multiple-input multiple-output (MIMO) ad-hoc networks. Multiple-packet receptions in MIMO systems have attracted as a key technique to achieve a high transmission rate. In the conventional protocols for multiple-packet receptions, timing offsets among multiple-frame transmissions cause frame collisions induced by hidden nodes, which degrades network performance. In the proposed protocol, transmission synchronization among hidden nodes can be achieved by applying pulse/tone exchanges. By applying the pulse/tone exchanges, multiple-packet receptions among hidden nodes can be achieved, which enhances network throughputs compared with the conventional protocol. Simulation results show effectiveness of the proposed protocol.

• International journal of advanced smart convergence
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• 제9권2호
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• pp.58-67
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• 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.