Adaptive Radio Resource Control via Cascaded Neural Networks for Sequenced Propagation Estimation and Multi-user Detection in Third-generation Wireless Networks

Abstract

A hybrid neural network approach is presented to predict 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 three performance parameters influence the quality of service (QoS) for multimedia services for 3G networks. These networks are based on hierarchical cell structures and operate in mobile urban and indoor environments with service demands emanating from diverse traffic sources. Candidate radio interfaces for these networks employ a form of wideband CDMA.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 variablerate 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 handoff procedures. In the final stage, the SOFM, operating in a hybrid continuous and discrete space, adaptively allocates resources of antenna-based cell sectorization, activity monitoring, variable-rate coding, power control, handoff and caller admission to meet the QoS for various multimedia services.The performance of the NN cascade is evaluated through simulation of a candidate 3G network using W-CDMA parameters in a small-cell environment. The simulated network consists of a representative number of cells. QoS requirements for different classes of multimedia services are considered. Initial results show the cascade yields relatively low probability of new call blocking and handoff dropping.