Radio Resource Management for Wireless Networks
Radio Resource Management for Wireless Networks
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Radio Network Planning and Optimisation for Umts
Radio Network Planning and Optimisation for Umts
Fundamentals of Cellular Network Planning and Optimisation: 2G/2.5G/3G... Evolution to 4G
Fundamentals of Cellular Network Planning and Optimisation: 2G/2.5G/3G... Evolution to 4G
Modular system-level simulator concept for OFDMA systems
IEEE Communications Magazine
Dynamic multiuser resource allocation and adaptation for wireless systems
IEEE Wireless Communications
Asymptotically fair transmission scheduling over fading channels
IEEE Transactions on Wireless Communications
Opportunistic beamforming using dumb antennas
IEEE Transactions on Information Theory
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To dimension cellular wireless networks, accurate estimates of the cell throughput have to be available. Consideration of all requirements of future packet-switched networks, especially the impact of scheduling, leads to extensive system level simulations that have to be performed in order to obtain the cell throughput. A semi-analytical methodology is proposed in this paper that is able to give average cell throughput estimates for given network layouts without performing extensive system level simulations. The signal to interference ratio (SIR) probability density function (pdf) which reflects the behavior that is achieved after scheduling of users is derived. Based on the SIR pdf, probabilities for the usage of modulation and coding schemes are obtained and the average cell throughput is calculated. Results are presented for well known scheduling algorithms and a channel model that is valid for networks utilizing frequency diversity by distributing the subcarriers over the whole system bandwidth like the partial usage of subchannels (PUSC) mode in IEEE 802.16e. It is shown that the average cell throughput estimates are within 10 % of the average cell throughput that is obtained by system level simulations which model all the properties including scheduling in detail. Due to the usage of analytical expressions, results can be obtained in less than a minute for the proposed methodology while a system level simulation usually takes several hours.