|dc.contributor.author||Hortos, William S.||
|dc.identifier.citation||Hortos, W. S. (1999). Cascaded neural networks for sequenced propagation estimation, multiuser detection, and adaptive radio resource control of third-generation wireless networks for multimedia services. Proceedings of SPIE - the International Society for Optical Engineering, 3722, 261-275.||en_US
|dc.description||Propagation channel estimation, multimedia services, multiuser detection, wireless communication networks,
Kohonen self-organizing feature maps, Hopfield neural networks, multilayer perceptron neural networks||en_US
|dc.description.abstract||A hybrid neural network approach is presented to estimate radio propagation characteristics and multiuser interference and to
evaluate their combined impact on throughput, latency and information loss in third-generation (3G) wireless networks. The
latter three performance parameters influence the quality of service (QoS) for multimedia services under consideration for 3G
networks. These networks, based on a hierarchical architecture of overlaying macrocells on top of micro- and picoells, are
planned to operate in mobile urban and indoor environments with service demands emanating from circuit-switched, packetswitched
and satellite-based traffic sources. Candidate radio interfaces for these networks employ a form of wideband
CDMA in 5-MHz and wider-bandwidth channels, with possible asynchronous operation of the mobile subscribers.
The proposed neural network (NN) architecture allocates network resources to optimize QoS metrics. Parameters of the
radio propagation channel are estimated, followed by control of an adaptive antenna array at the base station to minimize
interference, and then joint multiuser detection is performed at the base station receiver. These adaptive processing stages are
implemented as a sequence of NN techniques that provide their estimates as inputs to a final-stage Kohonen self-organizing
feature map (SOFM). The SOFM optimizes the allocation of available network resources to satisfy QoS requirements for
variable-rate voice, data and video services. As the first stage of the sequence, a modified feed-forward multilayer perceptron
NN is trained on the pilot signals of the mobile subscribers to estimate the parameters of shadowing, multipath fading and
delays on the uplinks. A recurrent NN (RNN) forms the second stage to control base stations' adaptive antenna arrays to
minimize intra-cell interference. The third stage is based on a Hopfield NN (HNN), modified to detect multiple users on the
uplink radio channels to mitigate multiaccess interference, control carrier-sense multiple-access (CSMA) protocols, and
refine call handoff procedures. In the final stage, the Kohonen SOFM, operating in a hybrid continuous and discrete space,
adaptively allocates the resources of antenna-based cell sectorization, activity monitoring, variable-rate coding, power
control, handoff and caller admission to meet user demands for various multimedia services at minimum QoS levels.
The performance of the NN cascade is evaluated through simulation of a candidate 3G wireless network using W-CDMA
parameters in a small-cell environment. The simulated network consists of a representative number of cells. Mobile users
with typical movement patterns are assumed. QoS requirements for different classes of multimedia services are considered.
The proposed method is shown to provide relatively low probability of new call blocking and handoff dropping, while
maintaining efficient use of the network's radio resources.||en_US
|dc.rights||This published article is made available in accordance with publishers policy. It may be subject to U.S. copyright law.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).||en_US
|dc.title||Cascaded neural networks for sequenced propagation estimation, multiuser detection, and adaptive radio resource control of third-generation wireless networks for multimedia services||en_US