Single-Generation Network Coding for Networks with Delay

A single-source network is said to be memory-free if all of the internal nodes (those except the source and the sinks) do not employ memory but merely send linear combinations of the incoming symbols (received at their incoming edges) on their outgoing edges. Memory-free networks with delay using network coding are forced to do inter-generation network coding, as a result of which the problem of some or all sinks requiring a large amount of memory for decoding is faced. In this work, we address this problem by utilizing memory elements at the internal nodes of the network also, which results in the reduction of the number of memory elements used at the sinks. We give an algorithm which employs memory at all the nodes of the network to achieve single- generation network coding. For fixed latency, our algorithm reduces the total number of memory elements used in the network to achieve single- generation network coding. We also discuss the advantages of employing single-generation network coding together with convolutional network-error correction codes (CNECCs) for networks with unit- delay and illustrate the performance gain of CNECCs by using memory at the intermediate nodes using simulations on an example network under a probabilistic network error model.

Training-Embedded, Single-Symbol ML-Decodable, Distributed STBCs for Relay Networks

Recently, a special class of complex designs called Training-Embedded Complex Orthogonal Designs (TE-CODs) has been introduced to construct single-symbol Maximum Likelihood decodable (SSD) distributed space-time block codes (DSTBCs) for two-hop wireless relay networks using the amplify and forward protocol. However, to implement DSTBCs from square TE-CODs, the overhead due to the transmission of training symbols becomes prohibitively large as the number of relays increase. In this paper, we propose TE-Coordinate Interleaved Orthogonal Designs (TE-CIODs) to construct SSD DSTBCs. Exploiting the block diagonal structure of TE-CIODs, we show that the overhead due to the transmission of training symbols to implement DSTBCs from TE-CIODs is smaller than that for TE-CODs. We also show that DSTBCs from TE-CIODs offer higher rate than those from TE-CODs for identical number of relays while maintaining the SSD and full-diversity properties.

Quasi-Orthogonal Design and Performance Analysis of Amplify-And-Forward Relay Networks with Multiple-Antennas

This paper is on the design and performance analysis of practical distributed space-time codes for wireless relay networks with multiple antennas terminals. The amplify-andforward scheme is used in a way that each relay transmits a scaled version of the linear combination of the received symbols. We propose distributed generalized quasi-orthogonal space-time codes which are distributed among the source antennas and relays, and valid for any number of relays. Assuming M-PSK and M-QAM signals, we derive a formula for the symbol error probability of the investigated scheme over Rayleigh fading channels. For sufficiently large SNR, this paper derives closed-form average SER expression. The simplicity of the asymptotic results provides valuable insights into the performance of cooperative networks and suggests means of optimizing them. Our analytical results have been confirmed by simulation results, using full-rate full-diversity distributed codes.

Robust Relay Precoder Design for MIMO-Relay Networks

In this paper, we consider a robust design of MIMO-relay precoder and receive filter for the destination nodes in a non-regenerative multiple-input multiple-output (MIMO) relay network. The network consists of multiple source-destination node pairs assisted by a single MIMO-relay node. The source and destination nodes are single antenna nodes, whereas the MIMO-relay node has multiple transmit and multiple receive antennas. The channel state information (CSI) available at the MIMO-relay node for precoding purpose is assumed to be imperfect. We assume that the norms of errors in CSI are upper-bounded, and the MIMO-relay node knows these bounds. We consider the robust design of the MIMO-relay precoder and receive filter based on the minimization of the total MIMO-relay transmit power with constraints on the mean square error (MSE) at the destination nodes. We show that this design problem can be solved by solving an alternating sequence of minimization and worst-case analysis problems. The minimization problem is formulated as a convex optimization problem that can be solved efficiently using interior-point methods. The worst-case analysis problem can be solved analytically using an approximation for the MSEs at the destination nodes. We demonstrate the robust performance of the proposed design through simulations.

Experimental validation of analytical performance models for IEEE 802.11 networks

We consider the simplest IEEE 802.11 WLAN networks for which analytical models are available and seek to provide an experimental validation of these models. Our experiments include the following cases: (i) two nodes with saturated queues, sending fixed-length UDP packets to each other, and (ii) a TCP-controlled transfer between two nodes. Our experiments are based entirely on Aruba AP-70 access points operating under Linux. We report our observations on certain non-standard behavior of the devices. In cases where the devices adhere to the standards, we find that the results from the analytical models estimate the experimental data with a mean error of 3-5%.

On approximately universal schemes for two-hop networks

Full-duplex and half-duplex two-hop networks are considered. Explicit coding schemes which are approximately universal over a class of fading distributions are identified, for the case when the network has either one or two relays.

DMT of multi-hop cooperative networks

Some basic results that help in determining the Diversity-Multiplexing Tradeoff (DMT) of cooperative multihop networks are first identified. As examples, the maximum achievable diversity gain is shown to equal the min-cut between source and sink, whereas the maximal multiplexing gain is shown to equal the minimum rank of the matrix characterizing the MIMO channel appearing across a cut in the network. Two multi-hop generalizations of the two-hop network are then considered, namely layered networks as well as a class of networks introduced here and termed as K-parallel-path (KPP) networks. The DMT of KPP networks is characterized for K > 3. It is shown that a linear DMT between the maximum diversity dmax and the maximum multiplexing gain of 1 is achievable for fully-connected, layered networks. Explicit coding schemes achieving the DMT that make use of cyclic-division-algebra-based distributed space-time codes underlie the above results. Two key implications of the results in the paper are that the half-duplex constraint does not entail any rate loss for a large class of cooperative networks and that simple, amplify-and-forward protocols are often sufficient to attain the optimal DMT.

Enhancing lifetime of wireless sensor networks using multiple data sinks

In this paper, we address the fundamental question concerning the limits on the network lifetime in sensor networks when multiple base stations (BSs) are deployed as data sinks. Specifically, we derive upper bounds on the network lifetime when multiple BSs arc employed, and obtain optimum locations of the base stations that maximise these lifetime bounds. For the case of two BSs, we jointly optimise the BS locations by maximising the lifetime bound using genetic algorithm. Joint optimisation for more number of BSs becomes prohibitively complex. Further, we propose a suboptimal approach for higher number of BSs, Individually Optimum method, where we optimise the next BS location using optimum location of previous BSs. Individually Optimum method has advantage of being attractive for solving the problem with more number of BSs at the cost of little compromised accuracy. We show that accuracy degradation is quite small for the case of three BSs.

Minimizing buffer requirements under rate-optimal schedule in regular dataflow networks

Large-grain synchronous dataflow graphs or multi-rate graphs have the distinct feature that the nodes of the dataflow graph fire at different rates. Such multi-rate large-grain dataflow graphs have been widely regarded as a powerful programming model for DSP applications. In this paper we propose a method to minimize buffer storage requirement in constructing rate-optimal compile-time (MBRO) schedules for multi-rate dataflow graphs. We demonstrate that the constraints to minimize buffer storage while executing at the optimal computation rate (i.e. the maximum possible computation rate without storage constraints) can be formulated as a unified linear programming problem in our framework. A novel feature of our method is that in constructing the rate-optimal schedule, it directly minimizes the memory requirement by choosing the schedule time of nodes appropriately. Lastly, a new circular-arc interval graph coloring algorithm has been proposed to further reduce the memory requirement by allowing buffer sharing among the arcs of the multi-rate dataflow graph. We have constructed an experimental testbed which implements our MBRO scheduling algorithm as well as (i) the widely used periodic admissible parallel schedules (also known as block schedules) proposed by Lee and Messerschmitt (IEEE Transactions on Computers, vol. 36, no. 1, 1987, pp. 24-35), (ii) the optimal scheduling buffer allocation (OSBA) algorithm of Ning and Gao (Conference Record of the Twentieth Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, Charleston, SC, Jan. 10-13, 1993, pp. 29-42), and (iii) the multi-rate software pipelining (MRSP) algorithm (Govindarajan and Gao, in Proceedings of the 1993 International Conference on Application Specific Array Processors, Venice, Italy, Oct. 25-27, 1993, pp. 77-88). Schedules generated for a number of random dataflow graphs and for a set of DSP application programs using the different scheduling methods are compared. The experimental results have demonstrated a significant improvement (10-20%) in buffer requirements for the MBRO schedules compared to the schedules generated by the other three methods, without sacrificing the computation rate. The MBRO method also gives a 20% average improvement in computation rate compared to Lee's Block scheduling method.

Multipath routing to provide quality of service in mobile ad hoc networks

Because of frequent topology changes and node failures, providing quality of service routing in mobile ad hoc networks becomes a very critical issue. The quality of service can be provided by routing the data along multiple paths. Such selection of multiple paths helps to improve reliability and load balancing, reduce delay introduced due to route rediscovery in presence of path failures. There are basically two issues in such a multipath routing Firstly, the sender node needs to obtain the exact topology information. Since the nodes are continuously roaming, obtaining the exact topology information is a tough task. Here, we propose an algorithm which constructs highly accurate network topology with minimum overhead. The second issue is that the paths in the path set should offer best reliability and network throughput. This is achieved in two ways 1) by choice of a proper metric which is a function of residual power, traffic load on the node and in the surrounding medium 2) by allowing the reliable links to be shared between different paths.

Neural network based optimal routing algorithm for communication networks

This paper presents the capability of the neural networks as a computational tool for solving constrained optimization problem, arising in routing algorithms for the present day communication networks. The application of neural networks in the optimum routing problem, in case of packet switched computer networks, where the goal is to minimize the average delays in the communication have been addressed. The effectiveness of neural network is shown by the results of simulation of a neural design to solve the shortest path problem. Simulation model of neural network is shown to be utilized in an optimum routing algorithm known as flow deviation algorithm. It is also shown that the model will enable the routing algorithm to be implemented in real time and also to be adaptive to changes in link costs and network topology. (C) 2002 Elsevier Science Ltd. All rights reserved.

Calcium-Decorated Carbyne Networks as Hydrogen Storage Media

Among the carbon allotropes, carbyne chains appear outstandingly accessible for sorption and very light. Hydrogen adsorption on calcium-decorated carbyne chain was studied using ab initio density functional calculations. The estimation of surface area of carbyne gives the value four times larger than that of graphene, which makes carbyne attractive as a storage scaffold medium. Furthermore, calculations show that a Ca-decorated carbyne can adsorb up to 6 H(2) molecules per Ca atom with a binding energy of similar to 0.2 eV, desirable for reversible storage, and the hydrogen storage capacity can exceed similar to 8 wt %. Unlike recently reported transition metal-decorated carbon nanostructures, which suffer from the metal clustering diminishing the storage capacity, the clustering of Ca atoms on carbyne is energetically unfavorable. Thermodynamics of adsorption of H(2) molecules on the Ca atom was also investigated using equilibrium grand partition function.

Comparative Analysis of Pilot-Assisted Distributed Cophasing Approaches in Wireless Sensor Networks

This paper compares and analyzes the performance of distributed cophasing techniques for uplink transmission over wireless sensor networks. We focus on a time-division duplexing approach, and exploit the channel reciprocity to reduce the channel feedback requirement. We consider periodic broadcast of known pilot symbols by the fusion center (FC), and maximum likelihood estimation of the channel by the sensor nodes for the subsequent uplink cophasing transmission. We assume carrier and phase synchronization across the participating nodes for analytical tractability. We study binary signaling over frequency-flat fading channels, and quantify the system performance such as the expected gains in the received signal-to-noise ratio (SNR) and the average probability of error at the FC, as a function of the number of sensor nodes and the pilot overhead. Our results show that a modest amount of accumulated pilot SNR is sufficient to realize a large fraction of the maximum possible beamforming gain. We also investigate the performance gains obtained by censoring transmission at the sensors based on the estimated channel state, and the benefits obtained by using maximum ratio transmission (MRT) and truncated channel inversion (TCI) at the sensors in addition to cophasing transmission. Simulation results corroborate the theoretical expressions and show the relative performance benefits offered by the various schemes.

DMT of Wireless Networks: An overview

The e�cient operation of single-source, single-sink wireless network is considered with the diversity-multiplexing gain tradeo� (DMT) as the measure of performance. Whereas in the case of a point-to-point MIMO channel the DMT is determined by the fading statistics, in the case of a network, the DMT is additionally, a function of the time schedule according to which the network is operated, as well as the protocol that dictates the mode of operation of the intermediate relays.In general, it is only possible at present, to provide upper bounds on the DMT of the network in terms of the DMT of the MIMO channel appearing across cuts in the network. This paper presents a tutorial overview on the DMT of half-duplex multi-hop wireless networks that also attempts to identify where possible, codes that achieve the DMT.For example, it is shown how one can construct codes that achieve the DMT of a network under a given schedule and either an amplify-and-forward or decode-and-forward protocol. Also contained in the paper,are discussions on the DMT of the multiple-access channel as well as the impact of feedback on the DMT of a MIMO channel.

Limit Laws for Coverage in Backbone-Sensor Networks

We study the coverage in sensor networks having two types of nodes, sensor and backbone nodes. Each sensor is capable of transmitting information over relatively small distances. The backbone nodes collect information from the sensors. This information is processed and communicated over an ad-hoc network formed by the backbone nodes,which are capable of transmitting over much larger distances. We consider two modes of deployment of sensors, one a Poisson-Poisson cluster model and the other a dependently-thinned Poisson point process. We deduce limit laws for functionals of vacancy in both models using properties of association for random measures.