Minimum Number Of Transmissions Research Articles

Index Coded - NOMA in Vehicular Ad Hoc Networks

The demand for multimedia services is growing day by day in vehicular ad hoc networks (VANETs), resulting in high spectral usage and network congestion. Non-orthogonal multiple access (NOMA) is a promising wireless communication technique to solve the problems related to spectral efficiency effectively. The index coding (IC) is a powerful method to improve spectral utilization, where a sender aims to satisfy the needs of multiple receivers with a minimum number of transmissions. By combining these two approaches, in this work, we propose a novel technique called index coded NOMA (IC-NOMA), where we apply NOMA techniques on index coded data to reduce the number of transmissions further. This work shows that the IC-NOMA system demands a specific design for index codes to reap the advantages of NOMA. We have done the feasibility analysis of the proposed method in a general scenario and proposed an index code design to integrate IC over NOMA for the best efficiency. Through detailed analytical studies it is validated that the proposed transmission system provides improved spectral efficiency and power saving compared to conventional IC systems.

Index Coding with Multiple Interpretations.

The index coding problem consists of a system with a server and multiple receivers with different side information and demand sets, connected by a noiseless broadcast channel. The server knows the side information available to the receivers. The objective is to design an encoding scheme that enables all receivers to decode their demanded messages with a minimum number of transmissions, referred to as an index code length. The problem of finding the minimum length index code that enables all receivers to correct a specific number of errors has also been studied. This work establishes a connection between index coding and error-correcting codes with multiple interpretations from the tree construction of nested cyclic codes. The notion of multiple interpretations using nested codes is as follows: different data packets are independently encoded, and then combined by addition and transmitted as a single codeword, minimizing the number of channel uses and offering error protection. The resulting packet can be decoded and interpreted in different ways, increasing the error correction capability, depending on the amount of side information available at each receiver. Motivating applications are network downlink transmissions, information retrieval from datacenters, cache management, and sensor networks.

Embedded Index Coding With Consecutive Side Information in Vehicle to Vehicle Communication

Embedded index coding problem is a variant of index coding problems, where each user functions as both broadcast sender and receiver. Consider a set of the messages, the indices of which form an ordered set. Each user owns a subset of these messages known as side information and tries to meet the demands of one another with a minimum number of transmissions. The side information is said to be consecutive if the elements of the index set of side information at a user are consecutive. We consider a practical vehicular ad-hoc network where the embedded index coding could be applied. In the scenario considered, the receiver demands all messages it does not possess, and the side-information is consecutive. Under this setup, a lower bound on the number of transmissions is determined. We present an optimal solution to achieve the bound. The constructed codes work over any field size, including binary.

Sparse and Low-Rank Optimization for Pliable Index Coding via Alternating Projection

Pliable index coding (PICOD) has recently been regarded as a promising solution that exploits the coding advantage to improve communication efficiency of content-type systems (e.g., recommendation system), where clients are pliable and are interested in receiving any new message that they do not have. PICOD aims to find an effective coding strategy that satisfies the demands of all clients with the minimum number of transmissions. However, most of the previous works mainly provided theoretical understanding on PICOD in special instances based on greedy algorithms. In contrast, in this paper, we present a flexible sparse and low-rank matrix modeling approach to minimize the number of transmissions for the general PICOD problems. This is achieved by establishing generalized pliable alignment conditions to guarantee the requirements of all clients. As the resulting non-convex problem is highly intractable, we further develop an alternating pursuit framework to detect the rank of the matrix to be recovered by using the rank-increasing strategy. To address the feasibility-detection issues in the existing methods, we propose an alternating projection algorithm, which admits closed-form expressions and avoids excessive sparsity inducing. Moreover, we establish the global convergence of the alternating projection algorithm with random initial points. Simulation results demonstrate that the proposed alternating pursuit algorithm significantly reduces the number of transmissions compared to the state-of-the-art methods.

Taking the time for range testing: an approach to account for temporal resolution in acoustic telemetry detection range assessments

BackgroundIn acoustic telemetry studies, detection range is usually evaluated as the relationship between the probability of detecting an individual transmission and the distance between the transmitter and receiver. When investigating animal presence, however, few detections will suffice to establish an animal’s presence within a certain time frame. In this study, we assess detection range and its impacting factors with a novel approach aimed towards studies making use of binary presence/absence metrics. The probability of determining presence of an acoustic transmitter within a certain time frame is calculated as the probability of detecting a set minimum number of transmissions within that time frame. We illustrate this method for hourly and daily time bins with an extensive empirical dataset of sentinel transmissions and detections in a receiver array in a Belgian offshore wind farm.ResultsThe accuracy and specificity of over 84% for both temporal resolutions showed the developed approach performs adequately. Using this approach, we found important differences in the predictive performance of distinct hypothetical range testing scenarios. Finally, our results demonstrated that the probability of determining presence over distance to a receiver did not solely depend on environmental and technical conditions, but would also relate to the temporal resolution of the analysis, the programmed transmitting interval and the movement behaviour of the tagged animal. The probability of determining presence differed distinctly from a single transmission’s detectability, with an increase of up to 266 m for the estimated distance at 50% detection probability (D50).ConclusionWhen few detections of multiple transmissions suffice to ascertain presence within a time bin, predicted range differs distinctly from the probability of detecting a single transmission within that time bin. We recommend the use of more rigorous range testing methodologies for acoustic telemetry applications where the assessment of detection range is an integral part of the study design, the data analysis and the interpretation of results.

Joint Index Coding and Incentive Design for Selfish Clients

The index coding problem includes a server, a group of clients, and a set of data chunks. While each client wants a subset of the data chunks and already has another subset as its side information, the server transmits some (uncoded or coded) chunks to the clients over a noiseless broadcast channel. The objective of the problem is to satisfy the demands of all clients with the minimum number of transmissions. This paper investigates the index coding setting from a game-theoretical perspective. We consider selfish clients, where each selfish client has private side information and a private valuation of each data chunk it wants. In this context, our objectives are following: 1) to motivate each selfish client to reveal the correct side information and true valuation of each data chunk it wants; 2) to maximize the social welfare, i.e., the total valuation of the data chunks recovered by the clients minus the total cost incurred by the transmissions from the server. Our main contribution is to jointly develop coding and incentive schemes for achieving the first objective perfectly and achieving the second objective optimally or approximately with guaranteed approximation ratios (potentially within some restricted sets of coding matrices).

Index Coding in Vehicle to Vehicle Communication

Vehicle to Vehicle (V2V) communication phase is an integral part of collaborative message dissemination in vehicular ad-hoc networks (VANETs). In this work, we apply index coding techniques to reduce the number of transmissions required for data exchange. The index coding problem has a sender, which tries to meet the demands of several receivers in a minimum number of transmissions. All these receivers have some prior knowledge of the messages, known as the side-information. In this work, we consider a particular case of the index coding problem, where multiple nodes want to share information among them. Under this set up, lower bound on the number of transmissions is established when the cardinality of side-information is the same. An optimal solution to achieve the bound in a special case of VANET scenario is presented. For this special case, we consider the link between the nodes to be error-prone, and in this setting, we construct optimal linear error correcting index codes.

Energy-Efficient Broadcast Scheduling Algorithm in Duty-Cycled Multihop Wireless Networks

Broadcasting is a fundamental function for disseminating messages in multihop wireless networks. Minimum-Transmission Broadcasting (MTB) problem aims to find a broadcast schedule with minimum number of transmissions. Previous works on MTB in duty-cycled networks exploit a rigid assumption that nodes have only active time slot per working cycle. In this paper, we investigated the MTB problem in duty-cycled networks where nodes are allowed arbitrary active time slots per working cycle (MTBDCA problem). Firstly, it is proved to be NP-hard and o(ln⁡Δ)-inapproximable, where Δ is the maximum degree in the network. Secondly, an auxiliary graph is proposed to integrate nodes’ active time slots into the network and a novel covering problem is proposed to exploit nodes’ multiple active time slots for scheduling. Then, a ln⁡(Δ+1)-approximation algorithm is proposed for MTBDCA and a (ln⁡(Δ+1)+Δ)-approximation algorithm is proposed for all-to-all MTBDCA. Finally, extensive experimental results demonstrate the efficiency of the proposed algorithm.

Characterizing the Number of Optimal Index Codes and Their Relation to Min–Max Probability of Error Performance

An index coding problem arises when there is a single source with a number of messages and multiple receivers each wanting a subset of messages knowing a different set of messages a priori . The noiseless index coding problem is to identify the minimum number of transmissions (optimal length) to be made by the source through a noiseless channel so that all receivers can decode their wanted messages using the transmitted symbols and their respective prior information. Recently (A. Thomas, R. Kavitha, A. Chandramouli, and B. Sundar Rajan, “Optimal index coding with min-max probability of error over fading channels,” in Proc. IEEE 26th Annu. Int. Symp. Pers. Indoor Mobile Radio Commun. , Hong Kong, 2015, pp. 889–894), it is shown that different optimal length codes perform differently in a noisy channel for single-uniprior index coding problems. Towards identifying the best optimal length index code, one needs to know the number of optimal length index codes. In this paper, we consider unicast index coding problems and present results on the number of optimal length index codes making use of the representation of an index coding problem by an equivalent network code. Our formulation results in matrices of smaller sizes compared to the approach of Koetter and Medard (R. Koetter and M. Medard, “An algebraic approach to network coding,” IEEE/ACM Trans. Netw. , vol. 11, no. 5, pp. 782–795, Oct. 2003.). Our formulation leads to a lower bound on the minimum number of optimal length codes possible for all unicast index coding problems (L. Ong and C. K. Ho, “Optimal index codes for a class of multicast networks with receiver side information,” in Proc. IEEE Int. Conf. Commun. , 2012, pp. 2213–2218), which is met with equality for several special cases of the unicast index coding problem. Furthermore, for noisy broadcast channels, a method to identify the best among the optimal length codes for unicast index coding problems in terms of minimum–maximum error probability is presented.

Single Uniprior Index Coding With Min–Max Probability of Error Over Fading Channels

An index coding scheme in which the source (transmitter) transmits symbols over a wireless fading channel is considered. Index codes with the transmitter using minimum number of transmissions are known as optimal index codes. Different optimal index codes give different performances in terms of probability of error in a fading environment, and this also varies from receiver to receiver. In this paper, we deal with optimal index codes, which minimizes the maximum probability of error among all the receivers. We identify a criterion for optimal index codes that minimizes the maximum probability of error among all the receivers. For a special class of index coding problems, we give an algorithm to identify optimal index codes which minimize the maximum error probability. We illustrate our techniques and claims with simulation results leading to conclude that a careful choice among the optimal index codes will give a considerable gain in fading channels.

Minimum Broadcasting Structure for Optimal Data Dissemination in Vehicular Networks

In this paper, we model a vehicular multihop network as an evolving graph and formulate the problem of optimal data dissemination over the network in terms of minimum number of transmissions. We show that the problem belongs to the NP complexity class and provide an easy to implement polynomial-time 2 τH(Δ)-approximation algorithm, where τ is the number of different subgraphs that comprise the evolving graph, and H(Δ) is the harmonic number of the degree of the evolving graph. By means of applying our heuristic over a vehicular scenario generated by a microscopic road-traffic simulator, we provide some insight into the data dissemination issue. In addition, the proposed algorithm is employed to benchmark a state-of-the-art communication protocol. We hope this paper will inspire more efficient heuristics and data dissemination solutions.

Packet scheduling with joint design of MIMO and network coding

In this paper, we propose a joint design of MIMO technique and network coding (MIMO-NC) and apply it to improve the performance of wireless networks. We consider a system in which the packet exchange among multiple wireless users is forwarded by a relay node. In order to enjoy the benefit of MIMO-NC, all the nodes in the network are mounted with two antennas and the relay node possess the coding capability. For the cross traffic flows among any four users, the relay node not only can receive packets simultaneously from two compatible users in the uplink (users-to-relay node), but also can mix up distinct packets for four destined users into two coded packets and concurrently send them out in the same downlink (relay node-to-users), so that the information content is significantly increased in each transmission. We formalize the problem of finding a schedule to forward the buffered data of all the users in minimum number of transmissions in such a system as a problem of finding a maximum matching in a graph. We also provide an analytical model on maximum throughput and optimal energy efficiency, which explicitly measures the performance gain of the MIMO-NC enhancement. Our analytical and simulation results demonstrate that system performance can be greatly improved by the efficient utilization of MIMO and network coding opportunities.

Time and Energy Complexity of Function Computation Over Networks

This paper considers the following network computation problem: <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> nodes are placed on a √n × √n grid, each node is connected to every other node within distance <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</i> ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> ) of itself, and it is assigned an arbitrary input bit. Nodes communicate with their neighbors and a designated sink node computes a function <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</i> of the input bits, where <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</i> is either the identity or a symmetric function. We first consider a model where links are interference and noise-free, suitable for modeling wired networks. Then, we consider a model suitable for wireless networks. Due to interference, only nodes which do not share neighbors are allowed to transmit simultaneously, and when a node transmits a bit, all of its neighbors receive an independent noisy copy of the bit. We present lower bounds on the minimum number of transmissions and on the minimum number of time slots required to compute <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</i> . We also describe efficient schemes that match both of these lower bounds up to a constant factor and are thus jointly (near) optimal with respect to the number of transmissions and the number of time slots required for computation. At the end of the paper, we extend results on symmetric functions to general network topologies, and obtain a corollary that answers an open question posed by El Gamal in 1987 regarding the computation of the parity function over ring and tree networks.

Going realistic and optimal: A distributed multi-hop broadcast algorithm for vehicular safety

A subject of great interest and important investments by governments, navigation system companies and street management authorities is highway safety. In this context, an important role is played by applications designed to warn drivers of upcoming dangers. An example is vehicular accident warning systems, which advertise accident events to approaching vehicles. The effectiveness of currently in use vehicular accident warning systems can be jeopardized by their: (a) inability to provide an accident warning to the closest approaching vehicles; and, (b) high delays in advertising an event. In fact, such systems are unable to reach the vehicles that are closest to an accident site due to the absence of any deployed automatic detection and broadcast mechanisms. The future deployment of Vehicular Ad hoc Networks (VANETs) can fill this gap. By leveraging on the distributed nature of ad hoc networks, accident warning systems can rapidly alert the vehicles which most risk their involvement in a crash. To reach this goal, VANET-based accident warning systems require the design of efficient broadcast algorithms. A number of solutions have been proposed in the past few years. However, no such proposals, to the best of our knowledge, assume realistic wireless propagation scenarios. The scope of this paper is to present an optimal distributed algorithm, working at the application layer, for the broadcast of safety messages in VANETs. Optimality, in terms of delay, is achieved in unidimensional highway scenarios and under realistic wireless propagation assumptions. This is the only algorithm, to this date, capable of reaching all vehicles with the minimum number of transmissions within a realistic setting.

A minimum transmission time encoding algorithm in multi-rate wireless networks

Network coding enables router nodes to perform coding operations besides replication and forwarding compared with traditional scheme. The minimum transmission time encoding problem in multi-rate wireless networks was investigated. Firstly, the problem is formulated as a minimum weighted clique partition of graph and proven to be NP-complete. Moreover, a heuristic minimum transmission rate first encoding (MTRFE) algorithm is proposed. The simulation results show that the MTRFE algorithm can decrease up to 16% the transmission time than the minimum number of transmissions encoding algorithm.

On multicast routing in wireless mesh networks

There are two fundamental approaches to multicast routing: shortest path trees (SPTs) and minimum cost trees (MCTs). The SPT algorithms minimize the distance (or cost) from the sender to each receiver, while the MCT algorithms such as minimum Steiner trees (MSTs) minimize the overall edge cost of the multicast tree. In wireless multi-hop networks, the tree cost can be redefined to exploit the wireless broadcast advantage: a minimum cost tree is one which connects sources and receivers by issuing a minimum number of transmissions (MNT). Among the different approaches, SPT is the more commonly used method for multicast routing in the Internet. The MNT approach was originally considered for energy-constrained wireless networks such as sensor and mobile ad-hoc networks. It is not clear how the different types of trees compare when used in WMNs. In this paper, we present a simulation-based performance comparison of SPTs, MSTs and MNT trees in WMNs using most concerned performance metrics such as packet delivery ratio, throughput, end-to-end delay, delay jitter and multicast traffic overheads. Based on the experimental results, we provide insights into the performance of multicast routing algorithms in WMNs and recommendations for suitable routing approaches.