Zhan P.,Quantenna Communications |
Yu K.,Ericsson AB |
Swindlehurst A.L.,University of California at Irvine
IEEE Transactions on Aerospace and Electronic Systems | Year: 2011
In this paper, we investigate a communication system in which unmanned aerial vehicles (UAVs) are used as relays between ground-based terminals and a network base station. We develop an algorithm for optimizing the performance of the ground-to-relay links through control of the UAV heading angle. To quantify link performance, we define the ergodic normalized transmission rate (ENTR) for the links between the ground nodes and the relay, and derive a closed-form expression for it in terms of the eigenvalues of the channel correlation matrix. We show that the ENTR can be approximated as a sinusoid with an offset that depends on the heading of the UAV. Using this observation, we develop a closed-form expression for the UAV heading that maximizes the uplink network data rate while keeping the rate of each individual link above a certain threshold. When the current UAV relay assignments cannot meet the minimum link requirements, we investigate the deployment and heading control problem for new UAV relays as they are added to the network, and propose a smart handoff algorithm that updates node and relay assignments as the topology of the network evolves. © 2006 IEEE.
Quantenna Communications | Date: 2011-01-12
Adjusting a Modulation and Coding Scheme (MCS) or more generally, Layer One parameters, for a data packet based on packet information and priority is disclosed. The packet information can typically be extracted from the packets header. Considering packet-specific information enables cross-layer optimization that can include consideration of packet error rate (PER) constraints, delay constraints, relative importance of packets within a data stream, beamforming (e.g., off or on, implicit or explicitlonger distances are more likely to merit implicit beamforming) constraints, and aggregation as a function of MCS or channel condition (more aggregation is generally desirable for higher MCS or better channels), to name several examples. It is also possible to differentiate drop probability based on the importance of frames like anchor frames, etc.
Quantenna Communications | Date: 2010-07-20
Deployment of wireless broadband and systems for use in providing wireless broadband is described. The system can include a trunk, which can include a root node, optional repeaters, and a main distribution node, the combination which enables wireless MIMO backhaul to a network such as the Internet.
Quantenna Communications | Date: 2015-06-16
A transceiver for a wireless local area network (WLAN) and the transceiver including a sounding feedback module and a sounding feedforward module. The sounding feedback module is responsive to an explicit sounding from a transmitting one of the nodes to send feedback of multiple-input multiple-output (MIMO) channel state information (CSI) derived from the channel sounding to the transmitting one of the nodes for improving subsequent transmissions. The sounding feedforward module is configured to monitor changes in CSI since the last explicit sounding based on CSI determined from the subsequent transmissions of the transmitting one of the nodes and responsive to a determination of a change in CSI above a threshold amount, to feedforward to the transmitting one of the nodes indicia of the change in CSI.
Quantenna Communications | Date: 2015-05-30
A diagnostic system for spatial diagnosis of the WLAN includes: a sounding aggregator and a spatial correlator. The sounding aggregator is configured to aggregate multiple-input multiple-output (MIMO) channel state information (CSI) from channel soundings of the WLAN, including channel soundings between a wireless access point (WAP) node and associated station nodes on a selected one of a plurality of communication channels of the WLAN. The spatial correlator is coupled to the sounding aggregator and configured to correlate CSI from the channel soundings with spatial characteristics of the WLAN including at least one of: a change in location of a WLAN node, human activity among the WLAN nodes, and structural impediments among WLAN nodes.