As various mobile communication systems have developed, dramatically integrated wireless network, where users can communicate seamlessly via several wireless access systems, have become expected. At present, there are many studies of integrated wireless network, but no study of a network design method. Therefore, in this paper, we discuss a network design method for integrated wireless networks. Because of the handover procedure, the network design where adjacent base stations are connected to the same router, regardless of radio system type, is simply considered. However, in such a design, where mobile users crowd into a particular area and users' access to the base stations located there increases, the load of these accesses is centralized to the single router. To overcome this problem, we propose a new network design wherein the base stations of heterogeneous wireless communication systems, the service areas of which overlap, are connected to a different router. In the proposed network design, although users' accesses are concentrated on the base stations located in a particular area, users in that area can be assigned bandwidth of several upper links according to the access conditions of the base stations in neighboring areas. Finally, we show the excellent performance of the proposed design by simulation experiments.

A lossless image compression method based on two-dimensional (2D) linear prediction with variable coefficients is proposed. This method employs a space varying autoregressive (AR) model. To achieve a higher compression ratio, the method introduces new ideas in three points: the level conversion, the fast recursive parameter estimation, and the switching method for coding table. The level conversion prevents an AR model from predicting gray-level which does not exist in an image. The fast recursive parameter estimation algorithm proposed here calculates varying coefficients of linear prediction at each pixel in shorter time than conventional one. For encoding, the mean square error between the predicted value and the true one is calculated in the local area. This value is used to switch the coding table at each pixel to adapt it to the local statistical characteristics of an image. By applying the proposed method to "Girl" and "Couple" of IEEE monochromatic standard images, the compression ratios of 100 : 46 and 100 : 44 have been achieved, respectively. These results are superior to the best results (100 : 61 and 100 : 57) obtained by the approach under JPEG recommendations.