Channel Characterization and Performance Evaluation of Mobile Communication Employing Stratospheric Platforms

Iskandar, Iskandar; Shimamoto, Shigeru

doi:10.1093/ietcom/e89-b.3.937

Cited by 66 publications

(31 citation statements)

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“…Firstly, in most wireless applications, it is usual to consider that the channel can be decomposed into two parts: the first part refers to the Line of Sight (LOS), which corresponds to the first term of the righthand side of (2), and the second part is associated with the non-line of sight (NLOS) components of the channel, which corresponds to the second term of the righthand side of (2). The knowledge of K, Σ, and h d at both sides is motivated by the fact that the coherence times corresponding to K, Σ, and h d are much larger than that of h r [9], [10], [11], [12]. Secondly, even when the Rice model does not hold true, it is often possible to decompose h as depicted in Eq.…”

Section: B Channel Modelmentioning

confidence: 99%

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Training Sequence Optimization for Joint Channel and Frequency Offset Estimation

Ciblat

Bianchi

Ghogho

2008

IEEE Trans. Signal Process.

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Abstract-We consider single-carrier and single-user transmissions over a frequency-selective channel. We address the problem of joint estimation of the channel and the carrier frequency offset using a known training sequence (TS). Since in general the TS that is optimum for CFO estimation is not optimum for channel estimation, here we design the TS to minimize the MeanSquare Error on the soft estimates of the data symbols obtained using a Wiener equalizer after CFO compensation. Our design results apply to the general scenarios of correlated and/or Ricean channel taps. Simulations measuring the bit error rate show an interesting gain when using the proposed training schemes in lieu of standard schemes.

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Section: B Channel Modelmentioning

confidence: 99%

“…assumption in [6] may be restrictive in practice (see e.g. [9], [10], [11], [12].) A correlation between the CIR coefficients will render the channel statistically frequencyselective, in which case there is no reason to expect a white TS to be optimal.…”

Section: Introductionmentioning

confidence: 99%

Training Sequence Optimization for Joint Channel and Frequency Offset Estimation

Ciblat

Bianchi

Ghogho

2008

IEEE Trans. Signal Process.

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“…The coverage diameter can be obtained by using equation 1) (Iskandar and Shimamoto, 2006), and (Iskandar and Putro, 2008).…”

Section: Methodsmentioning

confidence: 99%

Wireless Sensor Network Exploiting High Altitude Platform in 5G Network [Jaringan Sensor Nirkabel Menggunakan High Altitude Platform pada Jaringan 5G]

Mahyastuty¹,

Iskandar²,

Hendrawan³

2017

bul. pos. dan telekomun.

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A B S T R A C TKeywords: 5G HAP MTC WSN energy consumption Technology development and socio-economic transformation have increased the demand for 5G cellular networks. They are expected to send information quickly and support many use cases emerging from a variety of applications. One of the use cases on the 5G network is the massive MTC (Machine Type Communication), wherein wireless sensor network (WSN) is a typical application. Challenges faced by a 5G cellular network are how to model an architecture/topology to support WSN and to solve energy consumption efficiency problem in WSN. So, to overcome these challenges, a HAP system integrated with WSN which uses Low Energy Adaptive Hierarchy routing protocol is implemented. The HAP system is designed to be used at a 20-km altitude, and the topologies used are those with and without clustering. It uses 1,000 sensor nodes and Low Energy Adaptive Clustering Hierarchy protocol. This system was simulated using MATLAB. Simulations were performed to analyze the energy consumption, the number of dead nodes, and the average total packets which were sent to HAP for non-clustered topology and clustered topology. Simulation results showed that the clustered topology could reduce energy consumption and the number of dead nodes while increasing the total packet sent to HAP.

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“…Moreover, the relationship between the Rician factor of the Rician fading -link (12) and the satellite elevation ( ) was simulated in [49] through a large number of experiments. Then the relationship between the Rician factor and the satellite elevation ( ∈ [10 ∘ , 90 ∘ ]) was fitted as an empirical formula…”

Section: Satellite Elevation Error the Diagram Of Antenna Pointing Ementioning

confidence: 99%

Performance Analysis of Space Information Networks with Backbone Satellite Relaying for Vehicular Networks

Jiao

Gao

et al. 2017

Wireless Communications and Mobile Computing

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Space Information Network (SIN) with backbone satellites relaying for vehicular network (VN) communications is regarded as an effective strategy to provide diverse vehicular services in a seamless, efficient, and cost-effective manner in rural areas and highways. In this paper, we investigate the performance of SIN return channel cooperative communications via an amplify-andforward (AF) backbone satellite relaying for VN communications, where we assume that both of the source-destination and relaydestination links undergo Shadowed-Rician fading and the source-relay link follows Rician fading, respectively. In this SIN-assisted VN communication scenario, we first obtain the approximate statistical distributions of the equivalent end-to-end signal-to-noise ratio (SNR) of the system. Then, we derive the closed-form expressions to efficiently evaluate the average symbol error rate (ASER) of the system. Furthermore, the ASER expressions are taking into account the effect of satellite perturbation of the backbone relaying satellite, which reveal the accumulated error of the antenna pointing error. Finally, simulation results are provided to verify the accuracy of our theoretical analysis and show the impact of various parameters on the system performance.

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Channel Characterization and Performance Evaluation of Mobile Communication Employing Stratospheric Platforms

Cited by 66 publications

References 0 publications

Training Sequence Optimization for Joint Channel and Frequency Offset Estimation

Training Sequence Optimization for Joint Channel and Frequency Offset Estimation

Wireless Sensor Network Exploiting High Altitude Platform in 5G Network [Jaringan Sensor Nirkabel Menggunakan High Altitude Platform pada Jaringan 5G]

Performance Analysis of Space Information Networks with Backbone Satellite Relaying for Vehicular Networks

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