IEEE Journal on Selected Areas in Communications

We formulate and investigate fundamental problems that arise when multicast servers, that deliver content to multiple clients simultaneously, are replicated to enhance scalability and performance. Our study consists of two parts. First, we consider the problem under the assumption that the multicast clients are static for the duration of the multicast content distribution session. In this context, we examine two models for server behavior: fixed-rate servers, which transmit at a constant rate, and rate-adaptive servers, which adapt their transmission rate based on network conditions and/or feedback from clients. In both cases, we show that general versions of the client assignment problems are NP-hard. We then develop and evaluate efficient algorithms for interesting special cases, as well as heuristics for general cases. Second, we consider the case in which the set of clients changes dynamically during the multicast content distribution session. We again consider both fixed-rate and rate-adaptive servers. We formulate the problem as a Markov decision process, capturing the costs associated with trees, as well as the transition costs to dynamically change the trees. We use the properties of optimal solutions for small examples to develop a set of dynamic server selection heuristics.

A new macrocell prediction model for mobile radio environment is presented. The use of feedforward artificial neural networks makes it possible to overcome some important disadvantages of previous prediction models, including both deterministic and statistical types. Our sample implementation is based upon extensive electric field strength measurements (in the 900-MHz frequency band) that were carried out in the city of Belgrade using six different test transmitter locations. Comparison between the data obtained by the proposed electric field strength prediction model and independent measurement sets show that the proposed model is sufficiently accurate for use in planning mobile radio systems.

A three-dimensional model is proposed for simulating the wireless channel. The model allows simulation of the effects of realistic channels on space-time processing and coding systems. The model is characterized by a set of scattering centers with a given mean angle of arrival (departure), angle spread (azimuth and elevation), and propagation delay. Additionally, the model accommodates either transmitter or receiver motion. Spatial characteristics of the simulated channels match previously obtained analytical results. We use the model to generate standardized temporal and spatial channel conditions from Global System for Mobile communication and third-generation standards. We demonstrate the need for such a spatial description by contrasting our results to classic methods of generating these standardized channel conditions.

A novel stochastic channel model for the indoor propagation channel is presented. It is especially for, but not limited to future communication systems with multiple antennas like space division multiple access (SDMA), spatial filtering for interference reduction (SFIR), or multiple-input/multiple-output (MIMO). The model is designed for indoor scenarios, straight forward extendable to urban environments. It is based on physical wave propagation. The new approach describes the channel by multipath components, each characterized by its transfer matrix (including loss), delay, direction of arrival, and departure. The appearance and disappearance of multipath components over time is modeled as a birth and death process, a marked Poisson process. This enables first-time the correct modeling of spatial and temporal correlations. In each modeling step, path properties change according to the motion of transmitter and receiver. The changing delay times of propagation paths yield a realistic Doppler behavior of the channel. Deterministic ray tracing results are used to produce the huge data sets required for the statistical evaluation of the parameters of the proposed model. This method enables an automated parameter extraction for new environments or frequencies. The ray tracing tool has been verified by narrowband, wideband, and directional channel measurements. The novel stochastic spatial channel model allows the simulation of third-generation broadband radio systems including arbitrary antenna configurations and patterns. System simulations for the bit-error rate of radio links can be performed including intelligent antenna configurations like SDMA, SFIR, or MIMO. Furthermore, the capacity of complete systems can be investigated.

Theoretical and experimental studies of multiple-input/multiple-output (MIMO) radio channels are presented. A simple stochastic MIMO model channel has been developed. This model uses the correlation matrices at the mobile station (MS) and base station (BS) so that results of the numerous single-input/multiple-output studies that have been published in the literature can be used as input parameters. The model is simplified to the narrowband channels. The validation of the model is based upon data collected in both picocell and microcell environments. The stochastic model has also been used to investigate the capacity of MIMO radio channels, considering two different power allocation strategies, water filling and uniform and two different antenna topologies, 4/spl times/4 and 2/spl times/4. Space diversity used at both ends of the MIMO radio link is shown to be an efficient technique in picocell environments, achieving capacities within 14 b/s/Hz and 16 b/s/Hz in 80% of the cases for a 4/spl times/4 antenna configuration implementing water filling at a SNR of 20 dB.

This paper presents a multipath propagation model for microcells in urban areas. The proposed model is a statistical geometric model that describes the propagation characteristics for propagation loss, power delay profiles, and power azimuth spectra. The applicable target of the proposed model is long-term characteristics such as the characteristics that depend on the height of a base station (BS) and the distance between the BS and a mobile station. Calculated power delay profiles and power azimuth spectra based on the model are similar to those of the power function. In order to verify the validity of the model, the power delay profiles and power azimuth spectra are measured. The measurement results agree well with the simulation results based on the model and the validity of the model is confirmed.

We analyze the behavior of a multiple element antenna system in an indoor environment based on the measurements taken in the Lucent Bell Labs building in Crawford Hill, NJ, with a system of 12 transmitters and 15 receivers. In particular, we investigate the capacity behavior with respect to the polarization of the transmitting/receiving elements and the distance between the transmitting and the receiving arrays. The analysis of the power rolloff versus distance clearly demonstrates the different propagation characteristics of the horizontally versus the vertically polarized electric fields. Under strong line-of-sight (LOS) conditions (hallway environment), the power of the horizontally polarized waves falls off faster with distance than that of the vertically polarized fields. Also, the cross-polarization coupling is about -15 dB. Under nonline-of-sight (NLOS) conditions (labs), both polarizations display similar rolloff behavior with distance and the cross-polarization coupling is about 0 dB. There is a power loss of at least 15 dB under NLOS conditions relative to LOS conditions. The average received signal power affects the system capacity. In the hallway, horizontally polarized systems achieve lower capacities than their vertically polarized counterparts. Also the achievable capacity in the labs is much lower than that in the hallway, because of the lower average received power. The comparison of single polarization systems to hybrid polarization systems shows that combined polarization systems perform better in terms of achievable capacity. Therefore, there lies an advantage in using both electric field polarizations. However, under strong LOS conditions the channel itself inherently limits the capacity behavior of the system.