Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Cross-layer modelling for efficient transmission of non-realtime data traffic over downlink DS-CDMA heterogenous networks
AU - Navaie, Keivan
AU - Valaee, S.
AU - Sousa, E. S.
PY - 2005
Y1 - 2005
N2 - In this paper, we develop a cross-layer model for downlink interference in heterogenous DS-CDMA wireless cellular networks. In this model, interference is described as a function of application layer parameters (traffic characteristics) and physical layer variations (channel characteristics). We show that for a heterogenous service DS-CDMA network, downlink interference is a second-order self-similar process and thus has long-range dependence. We then use the predictive structure of total downlink interference to maximize non-realtime data throughput. We use fractional Gaussian noise (fGn) to model the self-similarity of downlink interference. In the proposed method, the base-station uses an optimal linear predictor, based on the fGn model, to estimate the level of interference. The estimated interference is then used to allocate power to users. To maximize data throughput, we use time domain scheduling. The simulation studies confirm the self-similarity of downlink interference and validate the fGn model. The simulation results also show a substantial performance improvement using the proposed predictive-adaptive scheme and confirm that the interference model is still valid after applying the proposed method.
AB - In this paper, we develop a cross-layer model for downlink interference in heterogenous DS-CDMA wireless cellular networks. In this model, interference is described as a function of application layer parameters (traffic characteristics) and physical layer variations (channel characteristics). We show that for a heterogenous service DS-CDMA network, downlink interference is a second-order self-similar process and thus has long-range dependence. We then use the predictive structure of total downlink interference to maximize non-realtime data throughput. We use fractional Gaussian noise (fGn) to model the self-similarity of downlink interference. In the proposed method, the base-station uses an optimal linear predictor, based on the fGn model, to estimate the level of interference. The estimated interference is then used to allocate power to users. To maximize data throughput, we use time domain scheduling. The simulation studies confirm the self-similarity of downlink interference and validate the fGn model. The simulation results also show a substantial performance improvement using the proposed predictive-adaptive scheme and confirm that the interference model is still valid after applying the proposed method.
KW - cross-layer modelling
KW - downlink interference
KW - DS-CDMA networks
KW - fractional Gaussian noise
KW - self-similar process
KW - time domain scheduling
U2 - 10.1109/WIMOB.2005.1512822
DO - 10.1109/WIMOB.2005.1512822
M3 - Conference contribution/Paper
SN - 0780391810
VL - 1
SP - 92
EP - 99
BT - WiMob'2005: IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, Vol 1, Proceedings
A2 - Pierre, S.
A2 - Conan, J.
PB - IEEE
CY - New York
T2 - IEEE International Conference on Wireless and Mobile Computing, Networking and Communications
Y2 - 22 August 2005 through 24 August 2005
ER -