Base station

About: Base station is a research topic. Over the lifetime, 85883 publications have been published within this topic receiving 1019303 citations. The topic is also known as: Mobile phone base stations & BS.

Downlink channel covariance matrix (DCCM) estimation and its applications in wireless DS-CDMA systems

Abstract: The downlink channel covariance matrix (DCCM) is of vital importance in determining downlink beamforming weights for base station (BS) antenna array systems. For the frequency-division-duplex (FDD) mode, DCCM is difficult to obtain due to a lack of direct measurement of downlink channel responses. In this paper, a novel technique is proposed for estimating DCCM using uplink channel responses only, which does not need direction-of-arrival (DOA) estimation and its association. The downlink beamforming scheme is then proposed for wireless DS-CDMA systems, using the obtained DCCM information together with the so-called virtual uplink beamforming and power control technique. Computer simulations show that using the BS antenna array together with this new beamforming technique can provide larger system capacity than traditional DOA-based approaches, which just direct the main beam toward the desired user.

Methods and apparatus for use in a wireless communications system that uses a multi-mode base station

Abstract: A multi-mode base station includes a transmit standby mode and an active mode. Transmit standby mode of base station operation is a low power/low interference level of operation as compared to active mode. In transmit standby mode at least some of the synchronization signaling such as pilot tone signaling is reduced in power level and/or rate with respect to the active mode. In transmit standby mode, the base station has no active state registered wireless terminals being serviced but may have some sleep state registered wireless terminals being serviced. Mode transitions from active to transmit standby may be in response to: a detected period of inactivity, scheduling information, base station mode change signals, and/or detected wireless terminal state transition. Mode transitions from transmit standby to active may be in response to: scheduling information, access signals, wake-up signals, hand-off signals, wireless terminal state change signals, and/or base station mode change signals.

Generalised sphere decoder for asymmetrical space-time communication architecture

Abstract: A generalised sphere decoding (GSD) algorithm is presented. Its application to the detection of information symbols in a multiantenna cellular system with N antennas at the mobile and M/spl ges/N antennas at the base station is explored. The GSD algorithm has the maximum likelihood (ML) performance for both the uplink and downlink with moderate complexity.

Pilot signal transmission for an orthogonal frequency division wireless communication system

Abstract: Transmission patterns for pilot symbols transmitted from a mobile station or base station are provided. The pattern allows for improved receipt of the pilot symbols transmitted. In addition, schemes for improving the ability to multiplex pilot symbols without interference and/ or biasing from different mobile stations over the same frequencies and in the same time slots.

Deep Reinforcement Learning Based Intelligent Reflecting Surface for Secure Wireless Communications

Abstract: In this paper, we study an intelligent reflecting surface (IRS)-aided wireless secure communication system for physical layer security, where an IRS is deployed to adjust its surface reflecting elements to guarantee secure communication of multiple legitimate users in the presence of multiple eavesdroppers. Aiming to improve the system secrecy rate, a design problem for jointly optimizing the base station (BS)'s beamforming and the IRS's reflecting beamforming is formulated given the different quality of service (QoS) requirements and time-varying channel condition. As the system is highly dynamic and complex, and it is challenging to address the non-convex optimization problem, a novel deep reinforcement learning (DRL)-based secure beamforming approach is firstly proposed to achieve the optimal beamforming policy against eavesdroppers in dynamic environments. Furthermore, post-decision state (PDS) and prioritized experience replay (PER) schemes are utilized to enhance the learning efficiency and secrecy performance. Specifically, PDS is capable of tracing the environment dynamic characteristics and adjust the beamforming policy accordingly. Simulation results demonstrate that the proposed deep PDS-PER learning-based secure beamforming approach can significantly improve the system secrecy rate and QoS satisfaction probability in IRS-aided secure communication systems.