Adaptive Modulation for Multiuser Amplify-and-Forward Relay Networks with Feedback Delays

Thilina, Karaputugala Madushan; Hossain, Ekram

doi:10.1109/glocom.2011.6133660

Cited by 2 publications

(4 citation statements)

References 17 publications

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“…Q(.) is the Q-function, x is the received SNR at the destination, and modulation level dependent parameter A l and a l are listed in Table II in [17]. …”

Section: Average Bermentioning

confidence: 99%

“…where ρ is the normalized correlation coefficient betweenγ can be derived in closedform as [17] fγ(K) (10) where φ = can be obtained in closed-form by integrating PDF ofγ (K) 1 as follows:…”

Section: A Cdf Of End-to-end Snrmentioning

confidence: 99%

“…Letγ (k) 1 be the delayed SNR at R k by a time delay T k of the perfect SNR γ (k) 1 , k = 1, 2, · · · , L. The joint PDF ofγ can be written as [16], [17] fγ(k)…”

Section: A Cdf Of End-to-end Snrmentioning

confidence: 99%

“…For M -QAM, the average BER adr can be calculated as [8], [11] BER adr = N n=1 b n P n,QAM N n=1 b n δ n (18) in which P n,QAM is the level specific average BER in [γ n , γ n+1 ] and can be derived in closed-form as [17] …”

Section: Average Bermentioning

confidence: 99%

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Selective relaying in multi-relay networks with feedback delays and adaptive modulation

Thilina¹,

Hossain²

2012

2012 IEEE International Conference on Communications (ICC)

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This paper evaluates the performance of adaptive modulation in multi-relay networks with selective relaying, under Nakagami-m fading. In the system model, the source decides independently whether to forward the source message to the destination via the best (partial relay selection) relay path or direct path by comparing the end-to-end instantaneous signalto-noise ratio (SNR) at the destination, which is independent of the modulation scheme. Adaptive discrete-rate M -ary quadrature amplitude modulation with fixed switching thresholds is implemented by dividing the SNR region into five modes. In particular, impact of imperfect (outdated) channel estimation due to feedback delay is quantified for relay selection. We derive the cumulative distribution function for the upper-bound of endto-end SNR in closed-form. Further, lower-bounds of outage probability and average bit error rate, and upper-bound of spectral efficiency are derived in closed-forms. Monte Carlo simulation results validate our numerical analysis.

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“…Q(.) is the Q-function, x is the received SNR at the destination, and modulation level dependent parameter A l and a l are listed in Table II in [17]. …”

Section: Average Bermentioning

confidence: 99%

Section: A Cdf Of End-to-end Snrmentioning

confidence: 99%

“…Letγ (k) 1 be the delayed SNR at R k by a time delay T k of the perfect SNR γ (k) 1 , k = 1, 2, · · · , L. The joint PDF ofγ can be written as [16], [17] fγ(k)…”

Section: A Cdf Of End-to-end Snrmentioning

confidence: 99%