Effect of Mobility on the Outage and BER Performances of Digital Transmissions over Nakagami- Fading Channels

Aalo, Valentine A.; Mukasa, Constantine; Efthymoglou, George P.

doi:10.1109/tvt.2015.2421502

Cited by 80 publications

(51 citation statements)

References 14 publications

(28 reference statements)

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“…The mobility of the MU is subject to random way path model and the PDF of the distance between the AP and MU for 1D, 2D and 3D network topologies can be expressed as 13,22

f_{r} ((), r) = \sum_{m = 1}^{n} B_{m} \frac{r^{β_{m}}}{D^{β_{m} + 1}}, 0 \leq r \leq D,

where D is the maximum distance between the AP and MU. The parameters n , B m and β m depend on the number of dimensions considered in the network topology and are summarised in Table 1 22 …”

Section: Channel and Mobility Statistical Modelsmentioning

confidence: 99%

“…The model is mostly used due to its simplicity and stochastically describes the behaviour of the mobile unit in a given network area. Also, it appears to create realistic mobility patterns for the way user might move in 10,13 …”

Section: Introductionmentioning

confidence: 99%

“…In open literature, several researches have studied the performance of different wireless system in the context of user randomness mobility. The effect of mobility on the outage probability and average error rate of a digital wireless system over Nakagami‐ m fading channel was presented in Aalo et al 13 In Almehmadi and Badarneh, 14 the error rate performance of a coherent binary modulation schemes in a mobile wireless system over generalised fading channel impaired by generalised Gaussian noise was investigated. Also, the performance of a dual‐hop network with a mobile relay node in a Nakagami‐ m environment was analysed in Mukasa et al 12 The authors considered amplified‐and‐forward and decode‐and‐forward relaying protocols for the system under studied.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On the performance of underlay cognitive radio system with random mobility under imperfect channel state information

Odeyemi

Owolawi

Olakanmi

2020

Int J Communication

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Summary In this paper, the performance of an underlay cognitive radio system with random mobility and imperfect channel state information (CSI) is investigated. The mobile user (MU) utilises maximum ratio combining (MRC) and selection combining (SC) diversity techniques as signal reception to improve the quality of received signal‐to‐noise ratio (SNR). Under the Rayleigh fading, random waypoint mobility model is employed to characterised the effect of the MU random mobility on the system performance. Thus, novel probability density function (PDF) and cumulative distribution function (CDF) for the two considered diversity techniques are derived. Through these, the outage probability and average bit error rate (ABER) closed‐form analytical expressions are then obtained to quantify the system performance under the MRC and SC schemes. The results illustrate the effect of imperfect CSI, user mobility which is characterised by pathloss and the network topology on the system performance. Also, the results depict that MRC offers the system better performance compared with SC under the same system conditions. The accuracy of the derived analytical expressions is verified through Monte‐Carlo simulations.

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“…The mobility of the MU is subject to random way path model and the PDF of the distance between the AP and MU for 1D, 2D and 3D network topologies can be expressed as 13,22

f_{r} ((), r) = \sum_{m = 1}^{n} B_{m} \frac{r^{β_{m}}}{D^{β_{m} + 1}}, 0 \leq r \leq D,

where D is the maximum distance between the AP and MU. The parameters n , B m and β m depend on the number of dimensions considered in the network topology and are summarised in Table 1 22 …”

Section: Channel and Mobility Statistical Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On the performance of underlay cognitive radio system with random mobility under imperfect channel state information

Odeyemi

Owolawi

Olakanmi

2020

Int J Communication

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“…In mobile networks, the presence of mobility can induce time-varying characteristics into the received signal [1]. The variation caused by the user mobility together with the fluctuation in the channel gain generated by multi-path fading can degrade the performance [2].…”

Section: Introductionmentioning

confidence: 99%

Effect of User Mobility and Channel Fading on the Outage Performance of UAV Communications

Khuwaja

Chen

Zheng

2020

IEEE Wireless Commun. Lett.

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“…The relay has a limited coverage area much lower than a BTS but it can handle the signals between two distant D2D users, which improves the total achievable throughput especially for the users near to the cell boundary. Several relaying strategies have been proposed, including amplify-and-forward (AF) and decode-and-forward (DF) [2][3][4][5][6]. In DF, which is mentioned in this research, the relay decodes the received signal, re-encodes it, and finally sends it to the RX node of the D2D pair [2].…”

Section: Introductionmentioning

confidence: 99%

Outage Analysis of Energy Harvested Relay-Aided Device-to-Device Communications in Nakagami Channel

Moghaddam

2018

JCOMSS

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In this paper, a low-complexity closed-form formula for the outage probability of the energy-harvested direct and decode-and-forward (DF) relay-aided underlay device-to-device (D2D) communications in Nakagami fading channel is derived. By proposing a new procedure, the power splitting factor in simultaneous wireless information and power transfer (SWIPT) energy-harvesting system is easily found such that the transmit power of the transmitter node in the direct and the relay node in a relay-aided D2D communications is fixed in a pre-defined value. Using the proposed procedure, the obtained closed-form expression is valid for both energy-harvested and non-energyharvested scenarios. This formula is based on n-point generalized Gauss-Laguerre and m-point Gauss-Legendre solutions. It is shown that n is more effective than m for reducing the formula complexity. In addition to a good agreement between the simulation results and numerical analysis based on normalized mean square error (NMSE), it is indicated that (n, m)=(1, 4) and (n, m)=(1, 2) are the appropriate choices, respectively for 0.5≤ µ <0.7 and µ ≥0.7, where µ is the fading shape factor. As shown in this investigation, increasing the average distance between the D2D pair and cellular user introduces lower interference, which is the reason for decreasing the outage probability. Furthermore, it is clear that increasing the Nakagami fading shape factor is the reason for decreasing the depth of fading, its fluctuations and the outage probability. Index Terms-Device to device (D2D) communications, Decodeand-forward (DF), Energy harvesting (EH), Simultaneous wireless information and power transfer (SWIPT), Gauss-Legendre/Gauss-Laguerre, Nakagami, Outage probability. Research works [2, 3], obtained closed-form formulas for the outage probability of direct underlay/overlay D2D communications in a Rayleigh channel. In Ref. [7], the exact formulas for the outage probability of in-band direct D2D communications underlying cellular network in a Rayleigh channel were proposed. The proposed model considers two radio resources reuse scenarios, one-reuse and two-reuse. The authors of [8] exploited stochastic geometry, Laplace transforms, and probability density function (pdf) to calculate the outage probability in a tractable manner.

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Effect of Mobility on the Outage and BER Performances of Digital Transmissions over Nakagami- Fading Channels

Cited by 80 publications

References 14 publications

On the performance of underlay cognitive radio system with random mobility under imperfect channel state information

On the performance of underlay cognitive radio system with random mobility under imperfect channel state information

Effect of User Mobility and Channel Fading on the Outage Performance of UAV Communications

Outage Analysis of Energy Harvested Relay-Aided Device-to-Device Communications in Nakagami Channel

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