This document provides updates to IEEE Std 802.16's MIB for the MAC, PHY and asso- ciated management procedures in order to accommodate recent extensions to the standard.

IEEE Standard for Local and Metropolitan Area Networks Part 16: Air Interface for Fixed Broadband Wireless Access Systems Draft Amendment: Management Information Base Extensions

With the remarkable progress of cooperative communication technology in recent years, its transformation to vehicular networking is gaining momentum. Such a transformation has brought a new research challenge in facing the realization of cooperative vehicular networking (CVN). This paper presents a comprehensive survey of recent advances in the field of CVN. We cover important aspects of CVN research, including physical, medium access control, and routing protocols, as well as link scheduling and security. We also classify these research efforts in a taxonomy of cooperative vehicular networks. A set of key requirements for realizing the vision of cooperative vehicular networks is then identified and discussed. We also discuss open research challenges in enabling CVN. Lastly, the paper concludes by highlighting key points of research and future directions in the domain of CVN.

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Cooperative Vehicular Networking: A Survey

/pdf/nonorthogonal-multiple-access-for-5g-and-beyond-4b3xqqfqoe.pdf

Nonorthogonal multiple access for 5G and beyond

In the recent past, we have witnessed the adoption of different machine learning techniques for indoor positioning applications using WiFi, Bluetooth and other technologies. The techniques range from heuristically derived hand-crafted feature-based traditional machine learning algorithms, feature selection algorithms to the hierarchically self-evolving feature-based Deep Learning algorithms. The transient and chaotic nature of the WiFi/Bluetooth fingerprint data along with different signal sensitivity of different device configurations presents numerous challenges that influence the performance of the indoor localization system in the wild. This article is intended to offer a comprehensive state-of-the-art survey on machine learning techniques that have recently been adopted for localization purposes. Hence, we review the applicability of machine learning techniques in this domain along with basic localization principles, applications, and the underlying problems and challenges associated with the existing systems. We also articulate the recent advances and state-of-the-art machine learning techniques to visualize the possible future directions in the research field of indoor localization.

A Survey of Machine Learning Techniques for Indoor Localization and Navigation Systems

Passive radio-frequency identification (RFID) systems carry critical importance for Internet of Things (IoT) applications due to their energy harvesting capabilities. RFID-based position estimation, in particular, is expected to facilitate a wide array of location-based services for IoT applications with low-power requirements. In this paper, considering monostatic and bistatic configurations and 3-D antenna radiation pattern, we investigate the accuracy of received signal strength-based wireless localization using passive ultra high frequency RFID systems. The Cramer-Rao lower bound (CRLB) for the localization accuracy is derived, and is compared with the accuracy of maximum likelihood estimators for various RFID antenna configurations. Numerical results show that due to RFID tag/antenna sensitivity, and the directional antenna pattern, the localization accuracy can degrade at blind locations that remain outside of the RFID reader antennas’ main beam patterns. In such cases optimizing elevation angle of antennas are shown to improve localization coverage, while using bistatic configuration improves localization accuracy significantly.

IoT Localization for Bistatic Passive UHF RFID Systems With 3-D Radiation Pattern

In this paper, we focus on uplink scheduling with the practical constraints imposed by the Long-Term Evolution/Long-Term Evolution-Advanced (LTE/LTE-A) standard. We consider multimedia traffic generated by mobile users with heterogeneous quality-of-service (QoS) requirements. To tackle the resulting time and frequency problem, we then propose an adaptive and potential aware scheduling scheme (APASS), which is standard compliant and covers a wide range of scheduling objectives. This scheduling scheme is composed of three algorithms, which work jointly to provide an efficient solution. Our performance evaluation shows that the APASS outperforms other state-of-the-art scheduling schemes in terms of user satisfaction and delay.

Standard-Compliant LTE-A Uplink Scheduling Scheme With Quality of Service

We propose a new access scheme for efficient support of multimedia services in OFDM wireless networks, both in the uplink and in the downlink. This scheme further increases the benefits of opportunistic scheduling by extending this cross-layer technique to higher layers. Access to the medium is granted based on a system of weights that dynamically accounts for both the experienced QoS and the transmission conditions. This new approach enables the full support of multimedia services with the adequate traffic and QoS differentiation while maximizing the system capacity and keeping a special attention on fairness. Performance evaluation shows that the proposed access technique outperforms existing wireless access schemes and demonstrates that choosing between high fairness and high system throughput is no more required.

https://link.springer.com/content/pdf/10.1155%2F2009%2F726495.pdf

A fair opportunistic access scheme for multiuser OFDM wireless networks

In wireless networks, providing a fair bandwidth allocation without too much reducing the system throughput is very challenging. Path loss attenuations induce unequal spectral efficiencies and in terms unequal throughtput for mobiles with different geographical positions. In the litterature, Proportional Fair (PF) is acknowledged as the reference scheduler in multiuser OFDM wireless networks. Opportunistically considering the channel state, PF is adapted to the wireless environment fighting the multipath fading negative effects. PF takes advantage of multiuser diversity and globally maximizes the throughput. Additionally, PF scheduling currently makes the best tradeoff between fairness and throughput maximization. However, severe fairness deficiencies appear when the mobiles experience unequal path loss. In this paper, we propose to solve this fairness issue with a modified PF scheme that introduces distance compensation factors. Simulation results show that this well-balanced resource allocation outperforms other existing scheduling schemes and jointly provides both high system throughput and high fairness.

Compensated Proportional Fair Scheduling in Multiuser OFDM Wireless Networks

Providing multimedia services in wireless networks requires maximizing the system throughput without sacrificing fairness. Previous works focus on system capacity optimization but fail to jointly ensure adequate fairness. This paper proposes a new MAC scheduling scheme which dynamically takes in consideration the QoS experienced by the mobiles and the transmission conditions in an extended cross-layer design. Based on a weighted opportunistic algorithm, our resource allocation takes a maximum advantage of multiuser diversity optimizing fairness and system throughput. This provides an efficient support of multimedia services in OFDM wireless networks. Performance evaluation shows that the proposed scheduling widely outperforms the best existing wireless OFDM based scheduling schemes.

Scheduling in OFDM Wireless Networks without Tradeoff between Fairness and Throughput

Localization of tagged objects with sufficient precision is a main issue in many industrial applications. In this paper, a new approach is proposed for the localization of UHF passive tags simply using the environment learning approach. This method uses, for a given passive tag located in a 2-D space, an aggregate function of the Received Signal Strength Indicator (RSSI) for all the possible RFID reader's transmission powers. Based on these measurements, we define a location signature, which is compared with those of other tags located at known positions in the neighborhood. We then implement a method based on the k-Nearest Neighbor (k-NN) algorithm to estimate the position of the target tag. Using a realistic test case involving seventy tags and four antennas, we show a very significant improvement of the localization accuracy in comparison with the results obtained using a single RSSI value.

Sébastien Baey

Papers

Standard-Compliant LTE-A Uplink Scheduling Scheme With Quality of Service

A fair opportunistic access scheme for multiuser OFDM wireless networks

Compensated Proportional Fair Scheduling in Multiuser OFDM Wireless Networks

Scheduling in OFDM Wireless Networks without Tradeoff between Fairness and Throughput

Accurate 2-D localization of RFID tags using antenna transmission power control