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 power control in a cellular mobile radio communications system

Abstract: The transmit power of a base station transmission to a mobile station is advantageously controlled. The base station receives a signal from the mobile station and determines a signal-to-interference ratio (SIR) associated with the received signal. The base station controls its transmit power to the mobile station using the determined SIR value in conjunction with a transmit power control command received from the mobile station. When the mobile station is in the process of a soft handover involving two or more base stations, each of those base stations determines an SIR value associated with a signal received from the mobile station. Moreover, each of the base stations controls its respective power using both the power control command received from the mobile station and the SIR determined by that base station. Similarly, when the mobile station is in the process of softer handover involving two or more sectors of a single base station, the SIR associated with a signal received from the mobile station in each of those base station sectors is determined and used to control the respective power of each base station sector in conjunction with a power control command received from the mobile station.

Method for efficiently transmitting physical channel in multi-carrier aggregation state to support broadband

Abstract: The present invention relates to a wireless connection system, and more specifically to a method for efficiently transmitting a control channel in a multi-carrier aggregation state. According to one aspect of the invention, a method for enabling a terminal to transmit data in a broadband wireless connection system that supports multiband comprises the steps of: receiving uplink acknowledgement information from a base station through a first downlink component carrier among plural downlink component carriers available in the terminal; transmitting data to the base station through an uplink resource indicated by the uplink acknowledge information; and receiving feedback information from the base station through the first control channel of the first downlink component carrier, wherein the feedback information indicates whether there is an error in the reception of the transmitted data.

Load balanced, energy-aware communications for Mars sensor networks

Abstract: The deployment and operation of self-organizing sensor networks is envisioned to play a key role in space exploration, such as for future in situ exploration of Mars. Sensors are equipped with several measurement instruments and are able to cooperate autonomously and to collect scientific measurements (seismic, chemicals, temperature, etc.). One or more landers or rovers functioning as base stations periodically (or on demand) collect measurements and relay the aggregated sensor field results to an orbiter and from the orbiter back to Earth. In this paper, we propose an efficient routing scheme for Mars sensor networks exploiting the similarity of operations between the wireless, multi-hop communications network connecting instruments (sensors) and rover(s) and the packet radio network used in a typical ad hoc networking environment. A critical issue in routing strategy design that sets the Mars sensor network apart from conventional ad hoc networks is energy conservation and prolonging network lifetime while maintaining connectivity and satisfying latency constraints. Simulation results show that with energy aware path selection, a more even distribution of energy consumption among nodes is developed and leads to longer network life time.

Millimeter Wave Cellular Wireless Networks: Potentials and Challenges

Abstract: Millimeter wave (mmW) frequencies between 30 and 300 GHz are a new frontier for cellular communication that offers the promise of orders of magnitude greater bandwidths combined with further gains via beamforming and spatial multiplexing from multi-element antenna arrays. This paper surveys measurements and capacity studies to assess this technology with a focus on small cell deployments in urban environments. The conclusions are extremely encouraging; measurements in New York City at 28 and 73 GHz demonstrate that, even in an urban canyon environment, significant non-line-of-sight (NLOS) outdoor, street-level coverage is possible up to approximately 200 m from a potential low power micro- or picocell base station. In addition, based on statistical channel models from these measurements, it is shown that mmW systems can offer more than an order of magnitude increase in capacity over current state-of-the-art 4G cellular networks at current cell densities. Cellular systems, however, will need to be significantly redesigned to fully achieve these gains. Specifically, the requirement of highly directional and adaptive transmissions, directional isolation between links and significant possibilities of outage have strong implications on multiple access, channel structure, synchronization and receiver design. To address these challenges, the paper discusses how various technologies including adaptive beamforming, multihop relaying, heterogeneous network architectures and carrier aggregation can be leveraged in the mmW context.

Placement and Power Allocation for NOMA-UAV Networks

Abstract: Unmanned aerial vehicles (UAVs) can be used as flying base stations to provide ubiquitous connections for mobile devices in over-crowded areas. On the other hand, non-orthogonal multiple access (NOMA) is a promising technique to support massive connectivity. In this letter, the placement and power allocation (PA) are jointly optimized to improve the performance of the NOMA-UAV network. Since the formulated joint optimization problem is non-convex, the location of the UAV is first optimized, with the total path loss from the UAV to users minimized. Then, the PA for NOMA is optimized using the optimal location of the UAV to maximize the sum rate of the network. Simulation results are presented to show the effectiveness and efficiency of the proposed scheme for NOMA-UAV networks.