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In this study, product of two independent and non-identically distributed (i.n.i.d.) random variables (RVs) for κ-µ fading distribution and α-µ fading distribution is considered. The statistics of the product of RVs has been broadly applied in a large number of communications fields, such as cascaded fading channels, multiple input multiple output (MIMO) systems, radar communications and cognitive radios (CR). Exact close-form expressions of probability density function (PDF) and cumulative distribution function (CDF) with exact series formulas for the product of two i.n.i.d. fading distributions κ-µ and α-µ are deduced more accurately to represent the provided product expressions and generalized composite multipath shadowing models. Furthermore, ergodic channel capacity (ECC) is obtained to measure maximum fading channel capacity. At last, interestingly unlike κ-µ, η-µ, α-µ in [9], [17], [18], these analytical results are validated with Monte Carlo simulations and it shows that for provided κ-µ/α-µ model, non-linear parameter has more important influence than multipath component in PDF and CDF, and when the ratio between the total power of the dominant components and the total power of the scattered waves is same, higher α can significantly improve channel capacity over composite fading channels.

- Publication
- IEICE TRANSACTIONS on Communications Vol.E103-B No.4 pp.458-466

- Publication Date
- 2020/04/01

- Publicized
- 2019/10/08

- Online ISSN
- 1745-1345

- DOI
- 10.1587/transcom.2019EBP3132

- Type of Manuscript
- PAPER

- Category
- Antennas and Propagation

He HUANG

Beijing University of Posts and Telecommuncations

Chaowei YUAN

Beijing University of Posts and Telecommuncations

The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.

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He HUANG, Chaowei YUAN, "Ergodic Capacity of Composite Fading Channels in Cognitive Radios with Series Formula for Product of κ-µ and α-µ Fading Distributions" in IEICE TRANSACTIONS on Communications,
vol. E103-B, no. 4, pp. 458-466, April 2020, doi: 10.1587/transcom.2019EBP3132.

Abstract: In this study, product of two independent and non-identically distributed (i.n.i.d.) random variables (RVs) for κ-µ fading distribution and α-µ fading distribution is considered. The statistics of the product of RVs has been broadly applied in a large number of communications fields, such as cascaded fading channels, multiple input multiple output (MIMO) systems, radar communications and cognitive radios (CR). Exact close-form expressions of probability density function (PDF) and cumulative distribution function (CDF) with exact series formulas for the product of two i.n.i.d. fading distributions κ-µ and α-µ are deduced more accurately to represent the provided product expressions and generalized composite multipath shadowing models. Furthermore, ergodic channel capacity (ECC) is obtained to measure maximum fading channel capacity. At last, interestingly unlike κ-µ, η-µ, α-µ in [9], [17], [18], these analytical results are validated with Monte Carlo simulations and it shows that for provided κ-µ/α-µ model, non-linear parameter has more important influence than multipath component in PDF and CDF, and when the ratio between the total power of the dominant components and the total power of the scattered waves is same, higher α can significantly improve channel capacity over composite fading channels.

URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2019EBP3132/_p

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@ARTICLE{e103-b_4_458,

author={He HUANG, Chaowei YUAN, },

journal={IEICE TRANSACTIONS on Communications},

title={Ergodic Capacity of Composite Fading Channels in Cognitive Radios with Series Formula for Product of κ-µ and α-µ Fading Distributions},

year={2020},

volume={E103-B},

number={4},

pages={458-466},

abstract={In this study, product of two independent and non-identically distributed (i.n.i.d.) random variables (RVs) for κ-µ fading distribution and α-µ fading distribution is considered. The statistics of the product of RVs has been broadly applied in a large number of communications fields, such as cascaded fading channels, multiple input multiple output (MIMO) systems, radar communications and cognitive radios (CR). Exact close-form expressions of probability density function (PDF) and cumulative distribution function (CDF) with exact series formulas for the product of two i.n.i.d. fading distributions κ-µ and α-µ are deduced more accurately to represent the provided product expressions and generalized composite multipath shadowing models. Furthermore, ergodic channel capacity (ECC) is obtained to measure maximum fading channel capacity. At last, interestingly unlike κ-µ, η-µ, α-µ in [9], [17], [18], these analytical results are validated with Monte Carlo simulations and it shows that for provided κ-µ/α-µ model, non-linear parameter has more important influence than multipath component in PDF and CDF, and when the ratio between the total power of the dominant components and the total power of the scattered waves is same, higher α can significantly improve channel capacity over composite fading channels.},

keywords={},

doi={10.1587/transcom.2019EBP3132},

ISSN={1745-1345},

month={April},}

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TY - JOUR

TI - Ergodic Capacity of Composite Fading Channels in Cognitive Radios with Series Formula for Product of κ-µ and α-µ Fading Distributions

T2 - IEICE TRANSACTIONS on Communications

SP - 458

EP - 466

AU - He HUANG

AU - Chaowei YUAN

PY - 2020

DO - 10.1587/transcom.2019EBP3132

JO - IEICE TRANSACTIONS on Communications

SN - 1745-1345

VL - E103-B

IS - 4

JA - IEICE TRANSACTIONS on Communications

Y1 - April 2020

AB - In this study, product of two independent and non-identically distributed (i.n.i.d.) random variables (RVs) for κ-µ fading distribution and α-µ fading distribution is considered. The statistics of the product of RVs has been broadly applied in a large number of communications fields, such as cascaded fading channels, multiple input multiple output (MIMO) systems, radar communications and cognitive radios (CR). Exact close-form expressions of probability density function (PDF) and cumulative distribution function (CDF) with exact series formulas for the product of two i.n.i.d. fading distributions κ-µ and α-µ are deduced more accurately to represent the provided product expressions and generalized composite multipath shadowing models. Furthermore, ergodic channel capacity (ECC) is obtained to measure maximum fading channel capacity. At last, interestingly unlike κ-µ, η-µ, α-µ in [9], [17], [18], these analytical results are validated with Monte Carlo simulations and it shows that for provided κ-µ/α-µ model, non-linear parameter has more important influence than multipath component in PDF and CDF, and when the ratio between the total power of the dominant components and the total power of the scattered waves is same, higher α can significantly improve channel capacity over composite fading channels.

ER -