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Upcoming standards are moving towards multi-antenna multiple-input multiple-output (MIMO) transmission techniques to harness the benefits of spatial degrees of freedom (DoF) in addition to the conventional time and frequency resources. Even though single user MIMO transmission improves the throughput noticeably, multiplexing different user data streams across the spatial dimension as in multiuser MIMO enhances the overall cell throughput significantly. However, this improved performance depends on the efficient selection of the users to be multiplexed over the spatial DoF.

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Location estimation in wireless communications systems experiencing mixed line-of-sight/non-line-of-sight (LOS/NLOS) or purely NLOS propagation paths is an open problem. In this paper, a novel least squares algorithm is presented to estimate the location of a mobile station (MS) experiencing mixed LOS/NLOS or purely NLOS communication with at least one base station (BS) by using the time of arrival (TOA), angle of arrival (AOA), and Doppler-shift (DS) measurements collected at the BS.

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In this paper, we propose an optimal relay transmission policy by using a stochastic energy harvesting (EH) model for the EH two-way relay network, wherein the relay is solar-powered and equipped with a finite-sized battery. In this policy, the long-term outage probability is minimized by adapting the relay transmission power to the wireless channel states, battery energy amount and causal solar energy states.

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An optimal transmission policy is considered for energy harvesting (EH) wireless point-to-point communications, wherein the source node is solar-powered and equipped with a finite-sized battery. The long-term outage probability is minimized by adapting the transmission power to the causal energy arrival information, battery energy amount and channel fading through a Markov decision process (MDP) framework.

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The use of energy harvesting cooperative relays is a promising solution to battery-limited wireless networks. In this paper, we consider a cooperative system in which one source node transmits data to one destination with the assistance of an energy harvesting decode-and-forward (DF) relay node. Our objective is to minimize the average symbol error rate (SER) performance, and a Markov decision process (MDP) is formulated to find the optimal stochastic power control at the relay that adapts the transmission power to the changes of energy harvesting, battery, channel and decoding states.

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