Increasing the DS/CDMA system reverse link capacity by equalizing the performance of different velocity users

Hashem, B.; Sousa, E.S.

doi:10.1109/icc.1998.685158

Cited by 10 publications

(17 citation statements)

References 6 publications

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“…, K) at the BS in cell 0. For the uplink of each user, we consider a similar receiver structure as that in [17]: a RAKE receiver is used with L fingers to collect the power from L independent equal strength Rayleigh fading. Since our intent is to focus on the impact of short-term fading, we assume that open loop power control compensates fully for long-term variations in the path loss.…”

Section: B Signal and Intra-cell Interference Modelmentioning

confidence: 99%

“…Due to the limited power adjustment step and frequency, the power level received at base station suffers a deviation from the mean value. Insightful studies on the statistics of received power level under imperfect power control have been conducted in [10][11] [17][18] 1 . It has been found in these studies that under imperfect power control, S ij is very well approximated by a lognormal random variable with mean u ij and variance γ ij .…”

Section: B Signal and Intra-cell Interference Modelmentioning

confidence: 99%

“…It has been found in these studies that under imperfect power control, S ij is very well approximated by a lognormal random variable with mean u ij and variance γ ij . The accuracy of this lognormal approximation was examined in [18] by comparing with the empirical received power probability density, and in [10] and [17] by comparing with the results of computer simulations, in both cases a very close match was presented. Let X ij be the decibel representation of S ij , i.e.…”

Section: B Signal and Intra-cell Interference Modelmentioning

confidence: 99%

“…where β = ln 10 10 . The parameter σ 2 ij reflects the imperfection degree of the power control and is determined by the fading rate and the receiver structure [17]. For the purpose of tractability, we assume all users in cell 0 have similar mobility and the same receiver structure so that σ 2 ij equals to σ 2 for all possible i and j.…”

Section: B Signal and Intra-cell Interference Modelmentioning

confidence: 99%

“…The inequality between variance is due to the fact that the power of the mobile user outside cell 0 is not controlled by BS0 [17]. Accordingly, the decibel representation of this interference is modeled as Gaussian random variable with mean n i and variance τ 2 , which have relations with v i and i in the same way as (1) and (2).…”

Section: Inter-cell Interference Modelmentioning

confidence: 99%

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Uplink capacity optimization by power allocation for multimedia cdma networks with imperfect power control

Shu

Niu

2003

IEEE J. Select. Areas Commun.

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A closed-form capacity quasi-optimal power allocation scheme is presented for the uplink of multimedia CDMA systems with randomized received SIR resulted from the errors of power control. The optimality in capacity comes from that this scheme provides class-dependent SIR margins subject to the constraint of differentiated outage requirements. The statistics of signal under imperfect power control is modeled as log-normal random variable. The objective of capacity maximization is formulated as the minimization of total average received powers since the capacity of a CDMA system is interference limited. Under this model, we first derive the necessary conditions that a capacity-optimal power allocation should satisfy. By using conservative bounds, we provide a closed-form approximate solution to this optimization problem. This approximate solution provides nearly the same admissible region for multimedia traffic under imperfect power control as the accurate solution (the optimal one) does. The closed-form quasi-optimal power allocation scheme proposed in this paper is just based on this approximate solution. By numerical example we verify our analysis and show that great capacity gain (e.g. 92% as a maximum in the example) can be achieved by our scheme over its counterpart.

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Section: B Signal and Intra-cell Interference Modelmentioning

confidence: 99%