Estimates of epsilon capacity for certain linear communication channels.
Epsilon capacity of linear communication channels, determining upper and lower bounds on rate of error free transmission
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Epsilon capacity of linear communication channels, determining upper and lower bounds on rate of error free transmission
The paper considers basic limitations on the amount of protocol information that must be transmitted in a data communication network to keep track of source and receiver addresses and of the starting and stopping of messages. Assuming Poisson message arrivals between each communicating source-receiver pair, a lower bound is found on the required protocol information for message. This lower bound is the sum of two terms, one for the message-length information, which depends only on the distribution of message lengths, and the other for the message-start information, which depends only on the product of the source-receiver pair arrival rate and the expected delay for transmitting the message. Two strategies are developed which, in the limit of large numbers of sources and receivers, almost meet the lower bound on protocol information.
A lower and an upper bound or manned space flight requirements for a data relay satellite system (DRSS) in the 1975-1980 time period are described. In all cases, the most stringent requirement is an intersatellite link to provide wideband information transfer from an overseas DRS to the Continental United States. A parametric communication analysis is made as a function of varying frequency and antenna aperture. The desirability of using a VHF frequency band for low data rates and voice relay and the requirement for frequencies of 8 and 16 GHz for video and wideband digital data relay are shown.
Error probability upper and lower bounds determined for self synchronized binary PSK communications systems, presenting maximum-likelihood and Monte Carlo computer simulation
High Altitude Platform Systems (HAPS) are emerging aircraft and balloon-type technology that can host payloads and provide services from the stratosphere. One potential HAPS use case is to provide wireless communication services for mobile devices, such as LTE, to wildland firefighters who often operate in locations without terrestrial wireless communications coverage. In this research we analyze historical wildland fire data to provide estimates of the annual number of HAPS required to support a fire season. We apply agglomerative clustering to group historical daily satellite-based fire observations where each cluster is analogous to a required HAPS vehicle. Our lower and upper bound estimates span a range of years, communication payload footprints, the minimum days of clusters prior to launch, and categories of fires. Additionally, we consider a case where HAPS vehicles can be transferred between fires after the initial fire has dissipated. In our specific case study from 2022 “Significant” fires (greater than 40,000 acres), we approximate that either 8 balloon HAPS vehicles without considering overprovisioning for station-keeping limitations or 23 fixed-wing aircraft would be required. Overprovisioning can scale the estimate for balloon vehicles based on reader preference, and for reference, Google Loon overprovisioned by 5-10x. Furthermore, in the case where budgets are constrained and not all of the estimated HAPS vehicles can be acquired, we provide operational insight on where to deploy HAPS vehicles. Generally, in the Spring months we see that HAPS vehicles are needed in the south and southeast of the US which transitions to the north and west as the fire season progresses.
In practical applications of importance sampling (IS) simulation, two basic problems are encountered, that of determining the estimation variance and that of evaluating the proper IS parameters needed in the simulations. The authors derive new upper and lower bounds on the estimation variance which are applicable to IS techniques. The upper bound is simple to evaluate and may be minimized by the proper selection of the IS parameter. Thus, lower and upper bounds on the improvement ratio of various IS techniques relative to the direct Monte Carlo simulation are also available. These bounds are shown to be useful and computationally simple to obtain. Based on the proposed technique, one can readily find practical suboptimum IS parameters. Numerical results indicate that these bounding techniques are useful for IS simulations of linear and nonlinear communication systems with intersymbol interference in which bit error rate and IS estimation variances cannot be obtained readily using prior techniques.
Lower bounds to minimum error probability using block coding on noisy discrete memoryless communication channels
The use is considered of massively parallel architectures to execute discrete-event simulations of what is termed self-initiating models. A logical process in a self-initiating model schedules its own state re-evaluation times, independently of any other logical process, and sends its new state to other logical processes following the re-evaluation. The interest is in the effects of that communication on synchronization. The performance is considered of various synchronization protocols by deriving upper and lower bounds on optimal performance, upper bounds on Time Warp's performance, and lower bounds on the performance of a new conservative protocol. The analysis of Time Warp includes the overhead costs of state-saving and rollback. The analysis points out sufficient conditions for the conservative protocol to outperform Time Warp. The analysis also quantifies the sensitivity of performance to message fan-out, lookahead ability, and the probability distributions underlying the simulation.
In this article, parallel computation of manipulator inverse dynamics is investigated. A hierarchical graph-based mapping approach is devised to analyze the inherent parallelism in the Newton-Euler formulation at several computational levels, and to derive the features of an abstract architecture for exploitation of parallelism. At each level, a parallel algorithm represents the application of a parallel model of computation that transforms the computation into a graph whose structure defines the features of an abstract architecture, i.e., number of processors, communication structure, etc. Data-flow analysis is employed to derive the time lower bound in the computation as well as the sequencing of the abstract architecture. The features of the target architecture are defined by optimization of the abstract architecture to exploit maximum parallelism while minimizing architectural complexity. An architecture is designed and implemented that is capable of efficient exploitation of parallelism at several computational levels. The computation time of the Newton-Euler formulation for a 6-degree-of-freedom (dof) general manipulator is measured as 187 microsec. The increase in computation time for each additional dof is 23 microsec, which leads to a computation time of less than 500 microsec, even for a 12-dof redundant arm.
Communication requirements of Cholesky factorization of dense and sparse symmetric, positive definite matrices are analyzed. The communication requirement is characterized by the data traffic generated on multiprocessor systems with local and shared memory. Lower bound proofs are given to show that when the load is uniformly distributed the data traffic associated with factoring an n x n dense matrix using n to the alpha power (alpha less than or equal 2) processors is omega(n to the 2 + alpha/2 power). For n x n sparse matrices representing a square root of n x square root of n regular grid graph the data traffic is shown to be omega(n to the 1 + alpha/2 power), alpha less than or equal 1. Partitioning schemes that are variations of block assignment scheme are described and it is shown that the data traffic generated by these schemes are asymptotically optimal. The schemes allow efficient use of up to O(n to the 2nd power) processors in the dense case and up to O(n) processors in the sparse case before the total data traffic reaches the maximum value of O(n to the 3rd power) and O(n to the 3/2 power), respectively. It is shown that the block based partitioning schemes allow a better utilization of the data accessed from shared memory and thus reduce the data traffic than those based on column-wise wrap around assignment schemes.
Recent work on the problem of mapping pipelined or parallel computations onto linear array, shared memory, and host-satellite systems is extended. It is shown how these problems can be solved even more efficiently when computation module execution times are bounded from below, intermodule communication times are bounded from above, and the processors satisfy certain homogeneity constraints. The improved algorithms have significantly lower time and space complexities than the more general algorithms: in one case, an O(nm3) time algorithm for mapping m modules onto n processors is replaced with an O(nm log m) time algorithm, and the space requirements are reduced from O(nm2) to O(m). Run-time complexity is reduced further with parallel mapping algorithms based on these improvements, which run on the architectures for which they create mappings.
An expurgated upper bound on the event error probability of trellis coded modulation is presented. This bound is used to derive a lower bound on the minimum achievable free Euclidean distance d sub (free) of trellis codes. It is shown that the dominant parameters for both bounds, the expurgated error exponent and the asymptotic d sub (free) growth rate, respectively, can be obtained from the cutoff-rate R sub O of the transmission channel by a simple geometric construction, making R sub O the central parameter for finding good trellis codes. Several constellations are optimized with respect to the bounds.
An energy-ratio function is introduced which greatly facilitates analysis and signal design for center-of-gravity feedback communication schemes. Using this function, we show that center-of-gravity feedback using regular-simplex signals achieves Shannon's lower bound on average energy per transmission for zero error probability if M, the number of messages, is 3, 4, or 5 and there is no constraint on system bandwidth.
The performance of bandwidth efficient trellis inner codes using two-dimensional MPSK signal constellations in a NASA concatenated coding is summarized. Work was also continued on trellis coded modulation using multi-dimensional signal sets. Achievable lower bounds on free distance trellis codes were proved and the existence of good trellis coded modulation (TCM) schemes were established for a variety of signal constellations. The performance of TCM schemes on fading channels is being investigated. Preliminary results indicate that bandwidth efficient trellis coding is feasible on such channels, but that the important design parameter is no longer the minimum free Euclidean distance.
Signals of opportunity (SoOp) reflectometry (SoOp-R) is a maturing field for geophysical remote sensing as evidenced by the growing number of airborne and spaceborne experiments. As this approach receives more attention, it is worth analyzing SoOp-R’s capabilities to retrieve subsurface soil moisture (SM) by leveraging communication and navigation satellite transmitters. In this research, the CRLB is used to identify the effects of variable SoOp-R parameters on the best achievable estimation error for root-zone soil moisture (RZSM). This study investigates the use of multiple frequency, polarization, and incidence angle measurement configurations on a two-layered dielectric profile. The results also detail the effects of variable SM conditions on the capability of SoOp-R systems to predict subsurface SM. The most prevalent observation is the importance of using at least two frequencies to limit uncertainties from subsurface SM estimates. If at least two frequencies are used, the CRLB of a profile is retrievable within the root-zone depending on the surface SM content as well as the number of independent measurements of the profile. For a depth of 30 cm, it is observed that a CRLB corresponding to 4% RZSM estimation accuracy is achievable with as few as 2 dual-frequency-based SoOp-R measurements. For this depth, increasing number of measurements provided by polarization and incidence angle allow for sensing of increasingly wet SM profile structures. This study, overall, details a methodology by which SoOp-R receiver system can be designed to achieve a desired CRLB using a trade-off study between the available measurements and SM profile.
The performance of NASA Telecommand System was analyzed. A random coding approach was taken to determine the optimum code rate to use in forward error correcting (FEC) system with a fixed signal energy to noise power density ration, but no bandwidth constraint. Capacity and cutoff rates of concatened coding systems were determined. A lower bound on the minium distance growth rate between unmerged codewords was obtained for time invarient convolutional codes.
In this paper the implementation of a parallel O(LogN) algorithm for computation of rigid multibody dynamics on a Hypercube MIMD parallel architecture is presented. To our knowledge, this is the first algorithm that achieves the time lower bound of O(LogN) by using an optimal number of O(N) processors. However, in addition to its theoretical significance, the algorithm is also highly efficient for practical implementation on commercially available MIMD parallel architectures due to its highly coarse grain size and simple communication and synchronization requirements. We present a multilevel parallel computation strategy for implementation of the algorithm on a Hypercube. This strategy allows the exploitation of parallelism at several computational levels as well as maximum overlapping of computation and communication to increase the performance of parallel computation.
Optical communication at the quantum limit requires that measurements on the optical field be maximally informative, but devising physical measurements that accomplish this objective has proven challenging. The Dolinar receiver exemplifies a rare instance of success in distinguishing between two coherent states: an adaptive local oscillator is mixed with the signal prior to photodetection, which yields an error probability that meets the Helstrom lower bound with equality. Here we apply the same local-oscillator-based architecture with aninformation-theoretic optimization criterion. We begin with analysis of this receiver in a general framework for an arbitrary coherent-state modulation alphabet, and then we concentrate on two relevant examples. First, we study a binary antipodal alphabet and show that the Dolinar receiver's feedback function not only minimizes the probability of error, but also maximizes the mutual information. Next, we study ternary modulation consistingof antipodal coherent states and the vacuum state. We derive an analytic expression for a near-optimal local oscillator feedback function, and, via simulation, we determine its photon information efficiency (PIE). We provide the PIE versus dimensional information efficiency (DIE) trade-off curve and show that this modulation and the our receiver combination performs universally better than (generalized) on-off keying plus photoncounting, although, the advantage asymptotically vanishes as the bits-per-photon diverges towards infinity.