Improved Spatial Modulation for High Spectral Efficiency

Spatial Modulation (SM) is a technique that can enhance the capacity of MIMO schemes by exploiting the index of transmit antenna to convey information bits. In this paper, we describe this technique, and present a new MIMO transmission scheme that combines SM and spatial multiplexing. In the basic form of SM, only one out of MT available antennas is selected for transmission in any given symbol interval. We propose to use more than one antenna to transmit several symbols simultaneously. This would increase the spectral efficiency. At the receiver, an optimal detector is employed to jointly estimate the transmitted symbols as well as the index of the active transmit antennas. In this paper we evaluate the performance of this scheme in an uncorrelated Rayleigh fading channel. The simulations results show that the proposed scheme outperforms the optimal SM and V-BLAST (Vertical Bell Laboratories Layered space-time at high signal-to-noise ratio (SNR). For example, if we seek a spectral efficiency of 8 bits/s/Hz at bit error rate (BER) of 10^-5, the proposed scheme provides 5dB and 7dB improvements over SM and V-BLAST, respectively.Comment: 7 pages, 4 figures, 1 table, International Journal of Distributed and Parallel Systems (IJDPS) Vol.3, No.2, March 201

Experimental study of bit error rate of free space optics communications in laboratory controlled turbulence

This paper reports experimental results for the performance of an free space optical (FSO) communication link employing different modulation schemes under the influence of the atmospheric scintillation. A dedicated experimental atmospheric simulation chamber has been developed where weak and medium turbulence can be generated and its effect on the FSO link is investigated. The experimental data obtained is compared to the theoretical prediction. The paper also shows that the effect on the data transmission performance depends on the position of turbulence source positioned within the chamber

On Minimizing the Maximum Broadcast Decoding Delay for Instantly Decodable Network Coding

In this paper, we consider the problem of minimizing the maximum broadcast decoding delay experienced by all the receivers of generalized instantly decodable network coding (IDNC). Unlike the sum decoding delay, the maximum decoding delay as a definition of delay for IDNC allows a more equitable distribution of the delays between the different receivers and thus a better Quality of Service (QoS). In order to solve this problem, we first derive the expressions for the probability distributions of maximum decoding delay increments. Given these expressions, we formulate the problem as a maximum weight clique problem in the IDNC graph. Although this problem is known to be NP-hard, we design a greedy algorithm to perform effective packet selection. Through extensive simulations, we compare the sum decoding delay and the max decoding delay experienced when applying the policies to minimize the sum decoding delay [1] and our policy to reduce the max decoding delay. Simulations results show that our policy gives a good agreement among all the delay aspects in all situations and outperforms the sum decoding delay policy to effectively minimize the sum decoding delay when the channel conditions become harsher. They also show that our definition of delay significantly improve the number of served receivers when they are subject to strict delay constraints

Completion Time Reduction in Instantly Decodable Network Coding Through Decoding Delay Control

For several years, the completion time and decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to completely act against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. In this paper, we study the effect of controlling the decoding delay to reduce the completion time below its currently best known solution. We first derive the decoding-delay-dependent expressions of the users' and overall completion times. Although using such expressions to find the optimal overall completion time is NP-hard, we design a novel heuristic that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Simulation results show that this new algorithm achieves both a lower mean completion time and mean decoding delay compared to the best known heuristic for completion time reduction. The gap in performance becomes significant for harsh erasure scenarios

Filtering Network Traffic Based on Protocol Encapsulation Rules

Packet filtering is a technology at the foundation of many traffic analysis tasks. While languages and tools for packet filtering have been available for many years, none of them supports filters operating on the encapsulation relationships found in each packet. This represents a problem as the number of possible encapsulations used to transport traffic is steadily increasing and we cannot define exactly which packets have to be captured. This paper presents our early work on an algorithm that models protocol filtering patterns (including encapsulation constraints) as Finite State Automata and supports the composition of multiple expressions within the same filter. The resulting, optimized filter is then translated into executable code. The above filtering algorithms are available in the NetBee open source library, which provides some basic tools for handling network packets (e.g., a tcpdump-like program) and APIs to build more advanced tool

Improving VANET Protocols via Network Science

Developing routing protocols for Vehicular Ad Hoc Networks (VANETs) is a significant challenge in these large, self- organized and distributed networks. We address this challenge by studying VANETs from a network science perspective to develop solutions that act locally but influence the network performance globally. More specifically, we look at snapshots from highway and urban VANETs of different sizes and vehicle densities, and study parameters such as the node degree distribution, the clustering coefficient and the average shortest path length, in order to better understand the networks' structure and compare it to structures commonly found in large real world networks such as small-world and scale-free networks. We then show how to use this information to improve existing VANET protocols. As an illustrative example, it is shown that, by adding new mechanisms that make use of this information, the overhead of the urban vehicular broadcasting (UV-CAST) protocol can be reduced substantially with no significant performance degradation.Comment: Proceedings of the 2012 IEEE Vehicular Networking Conference (VNC), Korea, November 201

Delivery Time Reduction for Order-Constrained Applications using Binary Network Codes

Consider a radio access network wherein a base-station is required to deliver a set of order-constrained messages to a set of users over independent erasure channels. This paper studies the delivery time reduction problem using instantly decodable network coding (IDNC). Motivated by time-critical and order-constrained applications, the delivery time is defined, at each transmission, as the number of undelivered messages. The delivery time minimization problem being computationally intractable, most of the existing literature on IDNC propose sub-optimal online solutions. This paper suggests a novel method for solving the problem by introducing the delivery delay as a measure of distance to optimality. An expression characterizing the delivery time using the delivery delay is derived, allowing the approximation of the delivery time minimization problem by an optimization problem involving the delivery delay. The problem is, then, formulated as a maximum weight clique selection problem over the IDNC graph wherein the weight of each vertex reflects its corresponding user and message's delay. Simulation results suggest that the proposed solution achieves lower delivery and completion times as compared to the best-known heuristics for delivery time reduction