This paper evaluates the ACRi Blind Beamforming (ABB) smart antenna algorithm which addresses the significant
problem caused by high-power transmitters located in close proximity to users. Current solutions are overwhelmed by
the rapid increase in number and variety of strong interference sources. ABB requires less computational complexity
than standard algorithms, making it feasible to be added to current and next-generation systems, and provides a highly
adaptive and reliable interference-resistant communications environment. Simulations show that ABB automatically
nulls jamming signals that are 20 dB to 40 dB stronger than the user signal, achieving close to the theoretically best
performance despite being a blind solution (no information required about the jammer or user signal) and its low
computational requirements. Systems with a limited number of antennas are evaluated because legacy and current
generation systems have as little as two antennas.
KEYWORDS: Antennas, Telecommunications, Signal to noise ratio, Robotic systems, Signal processing, Computer simulations, Field emission displays, Optical simulations, Mobile robots, Control systems
This paper describes and evaluates the beamforming performance for a flexible sparse array smart antenna system that
can be reconfigured through the use of multiple mobile robots. Current robotic systems are limited because they cannot
utilize beamforming due to their limited number of antennas and the high computational requirement of beamformers.
The beamforming techniques used in this paper are unique because unlike current beamformers, the antennas in the
sparse array are not connected together; instead, each robot has a single antenna. This work is made possible through
breakthroughs by the authors on ultra-low computational complexity beamforming and multi-mobile robot cluster
control. This new beamforming paradigm provides spatial reconfigurability of the array to control its location, size,
inter-antenna spacing and geometry via multi-robot collaborative communications. Simulation results evaluate the
effectiveness of smart antenna beamforming techniques when 1, 2, 3, 4, and 8 robots are utilized with and without
interference signals present.
This paper evaluates tracking and interference suppression performance for the ultra low computational complexity Non-
Eigen Decomposition (NED) blind beamforming algorithm. Current blind beamforming algorithms require
computational complexity too high for many target applications. NED does not rely on the eignenvalues and
eigenvectors used by conventional algorithms and requires significantly less computations, with a total computational
load of O(4M-4) per snapshot for a system with M receiving antennas by approximating the cross correlation vector of
the received signals in the reference and other antennas. This technique requires neither a training sequence nor an
assumption of incoherency among impinging signals. Simulations show that NED achieves comparable performance as
conventional blind beamforming algorithms in tracking, interference suppression, and misadjustment.
The performance of the fixed-user-per-slot allocation method and the dynamic slot allocation method for time slot allocation in SDMA (Space-Division Multiple Access) is evaluated. The unsorted/sorted first come first serve (USFCFS/SFCFS), first fit (FF) and modified first fit (MFF) methods are studied. Each slot allocation scheme is evaluated with a number of beamforming algorithms. Two different capacity efficiencies are defined as the thresholds in the slot assignment, with one threshold potentially achieving higher efficiency but sacrificing some of the benefits an adaptive antenna system can provide. The computational complexity of the algorithms is considered when evaluating their performance. We define a new performance indicator, the effective relative angle (ERA), and show that it can be used in evaluating not only the performance of the power gain achieved by the antenna array, but also the capacity efficiency. The system performance benefit of the sorting process for the fixed-user-per-slot allocation method is also studied. Theoretical and simulation results are examined to try to find a rule of thumb for the capacity improvement over a conventional (single antenna) system of an adaptive antenna system using each slot allocation method.
KEYWORDS: Antennas, Computer simulations, Local area networks, Standards development, Silicon, Computing systems, Information operations, Electrical engineering, System integration, Wireless communications
The Smart Wireless LAN (SWL) system integrates the Space- Division-Multiple-Access technique (also called smart antennas) with spread spectrum wireless LAN systems, such as IEEE 802.11 systems, to enable multiple wireless LAN users to transmit simultaneously in a frequency band. This advantage creates a potential problem because the 802.11 standard requires that all terminals use the same spreading code, so a straightforward application of the 802.11 standard could result in the loss of the 10 dB of spreading gain achieved by each terminal. This isn't a problem in a conventional system where only one user may transmit at a time in a frequency band, so the solution to this problem was created specifically for the SWL system. The Timing Synchronization Algorithms studied in this paper enable multiple (up to 11) users to use the same spreading code without a loss of the spreading gain. Two complimentary algorithms, in their sorted and unsorted formats, are studied in this paper and their simulation results are analyzed.
KEYWORDS: Signal to noise ratio, Antennas, Local area networks, Transmitters, Computer simulations, Wireless communications, Interference (communication), Computing systems, Electrical engineering, Video
Conventional wireless LAN (WLAN) protocols such as IEEE 802.11 allow only one user to transmit at a time in a frequency band. The Smart Wireless LAN (SWL) system adapts smart antenna systems for WLANs to enable multiple WLAN users to transmit simultaneously in a frequency band. Dynamic slot algorithms are used by SWL to improve transmission quality and maximize capacity by selecting users for time slots based on their unique spatial signatures (SS). These types of algorithms have not been studied much for conventional WLANs because only one user is allowed to transmit per time slot in those systems, eliminating the need for slot assignment. The simulation results, showing the tradeoffs of the various algorithms studied, are presented and analyzed. Experimental results studying the stability of the SS for a stationary transmitter and the variation of the SS with displacement are presented, and show the feasibility of using smart antennas with WLAN systems.
Spatial acquisition using the sun-lit Earth as a beacon source provides several advantages over active beacon-based systems for deep-space optical communication systems. However, since the angular extend of the Earth image is large compared to the laser beam divergence, the acquisition subsystem must be capable of resolving the image to derive the proper pointing orientation. The algorithms used must be capable of deducing the receiver location given the blurring introduced by the imaging optics and the large Earth albedo fluctuation. Furthermore, because of the complexity of modelling the Earth and the tracking algorithms, an accurate estimate of the algorithm accuracy can only be made via simulation using realistic Earth images. An image simulator was constructed for this purpose, and the results of the simulation runs are reported.
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