Topic
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.
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TL;DR: In this paper, a multi-cell multiple antenna system with precoding used at the base stations for downlink transmission is considered, where the precoding matrix used by the base station in one cell becomes corrupted by the channel between that base station and the users in other cells in an undesirable manner.
Abstract: This paper considers a multi-cell multiple antenna system with precoding used at the base stations for downlink transmission. For precoding at the base stations, channel state information (CSI) is essential at the base stations. A popular technique for obtaining this CSI in time division duplex (TDD) systems is uplink training by utilizing the reciprocity of the wireless medium. This paper mathematically characterizes the impact that uplink training has on the performance of such multi-cell multiple antenna systems. When non-orthogonal training sequences are used for uplink training, the paper shows that the precoding matrix used by the base station in one cell becomes corrupted by the channel between that base station and the users in other cells in an undesirable manner. This paper analyzes this fundamental problem of pilot contamination in multi-cell systems. Furthermore, it develops a new multi-cell MMSE-based precoding method that mitigate this problem. In addition to being a linear precoding method, this precoding method has a simple closed-form expression that results from an intuitive optimization problem formulation. Numerical results show significant performance gains compared to certain popular single-cell precoding methods.
1,040 citations
TL;DR: Joint power control and beamforming schemes are proposed for cellular systems where adaptive arrays are used only at base stations and the performances of these algorithms are compared with previously proposed algorithms through numerical studies.
Abstract: Joint power control and beamforming schemes are proposed for cellular systems where adaptive arrays are used only at base stations. In the uplink, mobile power and receiver diversity combining vectors at the base stations are calculated jointly. The mobile transmitted power is minimized, while the signal-to-interference-and-noise ratio (SINR) at each link is maintained above a threshold. A transmit diversity scheme for the downlink is also proposed where the transmit weight vectors and downlink power allocations are jointly calculated such that the SINR at each mobile is above a target value. The proposed algorithm achieves a feasible solution for the downlink if there is one and minimizes the total transmitted power in the network. In a reciprocal network it can be implemented in a decentralized system, and it does not require global channel response measurements. In a nonreciprocal network, where the uplink and downlink channel responses are different, the proposed transmit beamforming algorithm needs to be implemented in a centralized system, and it requires a knowledge of the downlink channel responses. The performances of these algorithms are compared with previously proposed algorithms through numerical studies.
985 citations
TL;DR: Analytical and computer simulation techniques are used to determine the performance of optimum combining when the received desired and interfering signals are subject to Rayleigh fading, and results show that optimum combining is significantly better than maximal ratio combining even when the number of interferers is greater than thenumber of antennas.
Abstract: This paper studies optimum signal combining for space diversity reception in cellular mobile radio systems. With optimum combining, the signals received by the antennas are weighted and combined to maximize the output signal-to-interference-plus-noise ratio. Thus, with cochannel interference, space diversity is used not only to combat Rayleigh fading of the desired signal (as with maximal ratio combining) but also to reduce the power of interfering signals at the receiver. We use analytical and computer simulation techniques to determine the performance of optimum combining when the received desired and interfering signals are subject to Rayleigh fading. Results show that optimum combining is significantly better than maximal ratio combining even when the number of interferers is greater than the number of antennas. Results for typical cellular mobile radio systems show that optimum combining increases the output signalto-interference ratio at the receiver by several decibels. Thus, systems can require fewer base station antennas and/or achieve increased channel capacity through greater frequency reuse. We also describe techniques for implementing optimum combining with least mean square (LMS) adaptive arrays.
942 citations
Patent•
05 Jun 1995
TL;DR: The Advanced Intelligent Network (AIN) wireline system connects to and controls processing of calls to a Personal Communication Service subscriber's wireless handset via a home base station or a wireless communication network as discussed by the authors.
Abstract: The Advanced Intelligent Network (AIN) wireline system connects to and controls processing of calls to a Personal Communication Service subscriber's wireless handset via a home base station or a wireless communication network. Depending on its current location, the subscriber's handset automatically registers with the base station or with a mobility controller of the wireless network. A new registration with the base station when the handset comes within range causes that station to update the subscriber's home location register in a central data base of the AIN. Similarly, when a handset first registers with a mobility controller, that controller updates the subscriber's home location register in the central data base of the AIN. In response to calls directed to the subscriber, the AIN accesses the home location register to determine the current location where the handset is registered. The AIN then uses that data to route the call to the current location. In response to calls from the handset, the central data base provides instruction data to the land line network and/or a mobility controller to extend a requested special service to the calling subscriber.
941 citations
13 Mar 2005
TL;DR: This paper suggests that the base station be mobile; in this way, the nodes located close to it change over time and the obtained improvement in terms of network lifetime is in the order of 500%.
Abstract: Although many energy efficient/conserving routing protocols have been proposed for wireless sensor networks, the concentration of data traffic towards a small number of base stations remains a major threat to the network lifetime. The main reason is that the sensor nodes located near a base station have to relay data for a large part of the network and thus deplete their batteries very quickly. The solution we propose in this paper suggests that the base station be mobile; in this way, the nodes located close to it change over time. Data collection protocols can then be optimized by taking both base station mobility and multi-hop routing into account. We first study the former, and conclude that the best mobility strategy consists in following the periphery of the network (we assume that the sensors are deployed within a circle). We then consider jointly mobility and routing algorithms in this case, and show that a better routing strategy uses a combination of round routes and short paths. We provide a detailed analytical model for each of our statements, and corroborate it with simulation results. We show that the obtained improvement in terms of network lifetime is in the order of 500%.
937 citations