Tactical communication systems based on civil standards: Modeling in the MiXiM framework

In this paper, new work is presented belonging to an ongoing study, which evaluates civil communication standards as potential candidates for the future military Wide Band Waveforms (WBWFs). After an evaluation process of possible candidates presented in [2], the selection process in [1] showed that the IEEE 802.11n OFDM could be a possible military WBWF candidate, but it should be further investigated first in order to enhance or even replace critical modules. According to this, some critical modules of the physical layer has been further analyzed in [3] regarding the susceptibility of the OFDM signal under jammer influences. However, the critical modules of the MAC layer (e.g., probabilistic medium access CSMA/CA) have not been analysed. In fact, it was only suggested in [2] to replace this medium access by the better suited Unified Slot Allocation Protocol - Multiple Access (USAP-MA) [4]. In this regard, the present contribution describes the design paradigms of the new MAC layer and explains how the proposed WBWF candidate has been modelled within the MiXiM Framework of the OMNeT++ simulator.Comment: Published in: A. F\"orster, C. Sommer, T. Steinbach, M. W\"ahlisch (Eds.), Proc. of 1st OMNeT++ Community Summit, Hamburg, Germany, September 2, 2014, arXiv:1409.0093, 201

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Efficient medium access control protocol for vehicular ad-hoc networks

Intelligent transportation systems (ITS) have enjoyed a tremendous growth in the last decade and the advancement in communication technologies has played a big role behind the success of ITS. Inter-vehicle communication (IVC) is a critical requirement for ITS and due to the nature of communication, vehicular ad-hoc network technology (VANET) is the most suitable communication technology for inter-vehicle communications. In Practice, however, VANET poses some extreme challenges including dropping out of connections as the moving vehicle moves out of the coverage range, joining of new nodes moving at high speeds, dynamic change in topology and connectivity, time variability of signal strength, throughput and time delay. One of the most challenging issues facing vehicular networks lies in the design of efficient resource management schemes, due to the mobile nature of nodes, delay constraints for safety applications and interference. The main application of VANET in ITS lies in the exchange of safety messages between nodes. Moreover, as the wireless access in vehicular environment (WAVE) moves closer to reality, management of these networks is of increasing concern for ITS designers and other stakeholder groups. As such, management of resources plays a significant role in VANET and ITS. For resource management in VANET, a medium access control protocol is used, which makes sure that limited resources are distributed efficiently. In this thesis, an efficient Multichannel Cognitive MAC (MCM) is developed, which assesses the quality of channel prior to transmission. MCM employs dynamic channel allocation and negotiation algorithms to achieve a significant improvement in channel utilisation, system reliability, and delay constraints while simultaneously addressing Quality of Service. Moreover, modified access priority parameters and safety message acknowledgments will be used to improve the reliability of safety messages. The proposed protocols are implemented using network simulation tools. Extensive experiments demonstrated a faster and more efficient reception of safety messages compared to existing VANET technologies. Finally, improvements in delay and packet delivery ratios are presented

Enabling Technologies for Ultra-Reliable and Low Latency Communications: From PHY and MAC Layer Perspectives

© 1998-2012 IEEE. Future 5th generation networks are expected to enable three key services-enhanced mobile broadband, massive machine type communications and ultra-reliable and low latency communications (URLLC). As per the 3rd generation partnership project URLLC requirements, it is expected that the reliability of one transmission of a 32 byte packet will be at least 99.999% and the latency will be at most 1 ms. This unprecedented level of reliability and latency will yield various new applications, such as smart grids, industrial automation and intelligent transport systems. In this survey we present potential future URLLC applications, and summarize the corresponding reliability and latency requirements. We provide a comprehensive discussion on physical (PHY) and medium access control (MAC) layer techniques that enable URLLC, addressing both licensed and unlicensed bands. This paper evaluates the relevant PHY and MAC techniques for their ability to improve the reliability and reduce the latency. We identify that enabling long-term evolution to coexist in the unlicensed spectrum is also a potential enabler of URLLC in the unlicensed band, and provide numerical evaluations. Lastly, this paper discusses the potential future research directions and challenges in achieving the URLLC requirements