Stochastic geometry and random graphs for the analysis and design of wireless networks
IEEE Journal on Selected Areas in Communications - Special issue on stochastic geometry and random graphs for the analysis and designof wireless networks
Spectrum sharing between cellular and mobile ad hoc networks: transmission-capacity trade-off
IEEE Journal on Selected Areas in Communications - Special issue on stochastic geometry and random graphs for the analysis and designof wireless networks
Transmission capacity of two-way communication in wireless ad hoc networks
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Rethinking MIMO for wireless networks: linear throughput increases with multiple receive antennas
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Adaptive spatial intercell interference cancellation in multicell wireless networks
IEEE Journal on Selected Areas in Communications - Special issue on cooperative communications in MIMO cellular networks
An overview of the transmission capacity of wireless networks
IEEE Transactions on Communications
| Hi-index | 754.84 |
Interference between nodes is a critical impairment in mobile ad hoc networks. This paper studies the role of multiple antennas in mitigating such interference. Specifically, a network is studied in which receivers apply zero-forcing beamforming to cancel the strongest interferers. Assuming a network with Poisson-distributed transmitters and independent Rayleigh fading channels, the transmission capacity is derived, which gives the maximum number of successful transmissions per unit area. Mathematical tools from stochastic geometry are applied to obtain the asymptotic transmission capacity scaling and characterize the impact of inaccurate channel state information (CSI). It is shown that, if each node cancels $L$ interferers, the transmission capacity decreases as $Theta big (epsilon ^{{ 1}over { L+1}}big)$ as the outage probability $epsilon $ vanishes. For fixed $epsilon $, as $L$ grows, the transmission capacity increases as $Theta big (L^{1- {{ 2}over { alpha }}}big)$ where $alpha $ is the path-loss exponent. Moreover, CSI inaccuracy is shown to have no effect on the transmission capacity scaling as $epsilon $ vanishes, provided that the CSI training sequence has an appropriate length, which we derive. Numerical results suggest that canceling merely one interferer by each node may increase the transmission capacity by an order of magnitude or more, even when the CSI is imperfect.