5G Internet of Things: A survey

Li, Shancang; Xu, Li Da; Zhao, Shanshan

doi:10.1016/j.jii.2018.01.005

Cited by 946 publications

(540 citation statements)

References 38 publications

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“…For orthogonal STBC designs the conditional SNR at the receiver can be given as Euclidean norm or the Frobenius norm of the channel times average SNR as in (1) [4]. 2 , sr sr sr F H  = (1) where sr  denotes the conditional SNR of the source-to-th r relay fading link, sr  denotes the average conditional SNR of the source-to-th r relay fading link and 2 sr F H denotes the Frobenius norm or 2 L norm. Every element of sr H is i.i.d.…”

Section: End-to-end Symbol Error Analysismentioning

confidence: 99%

“…The 5 th generation (5G) wireless communication systems will require a major paradigm shift to meet the increasing demand for reliable connectivity through high data rates, low latency, better energy efficiency, and Femto cell-based relays [1][2][3]. These relay nodes are equipped with energy harvesting (EH) techniques in the relaying network to improve energy efficiency.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of Selective-Decode and Forward Relaying Protocol over k-µ Fading Channel Distribution

Shankar¹,

Bhardwaj²,

Mishra³

2020

JTIT

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In this work, we examine the performance of selective-decode and forward (S-DF) relay systems over κ-µ fading channel condition. We discuss about the probability density function (PDF), system model, and cumulative distribution function (CDF) of κ-µ distributed envelope and signal to noise ratio (SNR) and the techniques to generate samples that follow κ-µ distribution. Specifically, we consider the case where the source-torelay (S→R), relay-to-destination (R→D) and source-to-destination (S→D) link is subject to the independent and identically distributed (i.i.d.) κ-µ fading. From the simulation results, the enhancement in the symbol error rate (SER) with a stronger line of sight (LOS) component is observed. This shows that S-DF relaying systems can perform well even in the non-fading or LOS conditions. Monte Carlo simulations are conducted for various values of fading parameters and the outcomes closely match with theoretical outcomes which validate the derivations.Keywords: multiple input multiple output, selective decode and forward, symbol error rate, channel fading, relaying protocol, signal to noise ratio, channel state information. IntroductionThe 5 th generation (5G) wireless communication systems will require a major paradigm shift to meet the increasing demand for reliable connectivity through high data rates, low latency, better energy efficiency, and Femto cell-based relays [1][2][3]. These relay nodes are equipped with energy harvesting (EH) techniques in the relaying network to improve energy efficiency. Cooperative communication is the natural choice for 5G wireless communication system, and it is adopted in 3 rd generation partnership project (3GPP), universal mobile telecommunications service (UMTS), long term evolution (LTE)-Advanced and IEEE 802.11 because the nodes in the cooperative communication network can share their resources with each other during the signal transmission [4][5][6]. Also, it is incorporated into numerous 5G wireless applications, such as machine-to-machine (M2M), device-to-device (D2D), cognitive radio (CR), high speed terrestrial network (HSTN) & free space optical (FSO) communication [7][8][9][10].Relay-assisted cooperation is the first step towards the 5G system that is expected to deliver up to 20Gbps in downlink (D/L) and 10Gbps in uplink (U/L) will be benchmarked by network operators during initial rollouts in the next few years [11][12]. The relay infrastructure does not need wired network connection, thus offering a reduction in the backhaul costs of the operator. Through the additional cooperative diversity inherent in such wireless systems, cooperative wireless communication significantly improves end-to-end reliability. If the direct source-to-destination (SD) channel is in a deep fade, the main advantage of the cooperative communication is that the destination node can still receive the source signal via the relay node.According to the signal receiving and transmitting, there are two basic methods of relaying: analog & digital. Analog relaying is also called no...

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Section: End-to-end Symbol Error Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of Selective-Decode and Forward Relaying Protocol over k-µ Fading Channel Distribution

Shankar¹,

Bhardwaj²,

Mishra³

2020

JTIT

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“…To try hands‐on experience on IoT concept and demonstrate the methods for setting up IoT environment over Internet, Pfister () sails through step‐by‐step process using .NET micro framework and Netduino Plus Board with some examples. For instance, to simulate data forwarding among nodes in IoT environment, it requires high level of interoperability (physical/virtual entities interacting each other) and demands hardware‐software usability to accomplish linking resources and synchronization of events (Li, Da Xu, & Zhao, ; Shahid & Aneja, ; Talavera et al, ; Yin, Zeng, Chen, & Fan, ). For example, Figure contains 10 elements, which are interconnected.…”

Section: Iot Data Processing Infrastructurementioning

confidence: 99%

Internet of Things: A primer

Paul

Jeyaraj

2019

Hum Behav & Emerg Tech

116

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We admire the emerging technologies that fascinate us, as it has become part of our daily life. Internet of Things (IoT) plays a major role in simplifying human effort. It leaps forward taking the advantages of latest wireless devices and communication technologies. IoT is a combination of technologies such as ubiquitous and pervasive computing, wireless communication devices and sensors, Internet protocol, and others. IoT logically interconnects and interoperates physical objects (sensors, wired/wireless communication devices) and virtual objects (web applications, virtual machines) over existing Internet infrastructure. IoT collects and records heterogeneous data (such as documents, images, videos, audios, and others) from heterogeneous applications (such as CCTV, medical images, barcode reader, and others) with the help of Internet. People, physical objects, and virtual objects are logically connected to the network to observe and analyze for decision‐making. Therefore, IoT has transformed to be an important evolving technology and inevitable in every sectors.

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“…[18][19][20] The larger the user's friend number is, the larger the influence of the user will be. [18][19][20] The larger the user's friend number is, the larger the influence of the user will be.…”

Section: Scoring Friendshipmentioning

confidence: 99%

Local experts finding using user comments in location‐based social networks

Cao

Yang

Cao

et al. 2019

Trans Emerging Tel Tech

Self Cite

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The opinions of local experts in the location‐based social network are of great significance to the collection and dissemination of local information. In this paper, we investigated in‐depth how the user comments can be used to identify the local expert over social networks. We first illustrate the existences of potential local experts in a social network using a scored model by considering the personal profiles, comments, friend relationship, and location preferences. Then, a multidimensional model is proposed to evaluate the local expert candidates and a local expert discovery algorithm is proposed to identify local experts. Meanwhile, a scoring algorithm is proposed to train the weights in the model. Finally, an expert recommendation list can be given based on the score ranks of the candidates. Experimental results demonstrate the effectiveness of proposed model and algorithms.

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5G Internet of Things: A survey

Cited by 946 publications

References 38 publications

Analysis of Selective-Decode and Forward Relaying Protocol over k-µ Fading Channel Distribution

Analysis of Selective-Decode and Forward Relaying Protocol over k-µ Fading Channel Distribution

Internet of Things: A primer

Local experts finding using user comments in location‐based social networks

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