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

Fast Handovers for Mobile IPv6 구현 및 Mobile IPv6 와의 성능 평가

Recent years have witnessed an explosion in wireless communications. In the last decades, the development of wireless communication systems and networks is taking us from a world where communications were mostly carried over PSTN, packet-switched and high speed LAN networks to one where the wireless transmission dominates. Nowadays, high data rates carry multimedia communications, real-time services for delay-sensitive applications are added and networks are asked to deal with a traffic mix of voice, data and video. Next generation mobile systems will further include a variety of heterogeneous access technologies, support multimedia applications and provide end-to-end IP connectivity (Bolton et al., 2007; Xylomenos et al., 2008; Demestichas et al., 2010). Undoubtedly, new possibilities are created for both telcos and users and important design and traffic issues emerge. This revolution has spurred scientists toward the development of reliable and computationally efficient models for evaluating the performance of wireless networks. A crucial parameter in the modeling of a cellular communication system is the shape of the cells. In real life, cells are irregular and complex shapes influenced by terrain features and artificial structures. However, for the sake of conceptual and computational simplicity, we often adopt approximate approaches for their design and modeling. In the published literature, cells are usually assumed hexagons or circles. The hexagonal approximation is frequently employed in planning and analysis of wireless networks due to its flexibility and convenience (Jan et al., 2004; Goldsmith, 2005; Pirinen, 2006; Chan & Liew, 2007; Hoymann et al., 2007; Baltzis, 2008, 2010a; Choi & You, 2008; Dou et al., 2008; Xiao et al., 2008; Baltzis & Sahalos, 2010). However, since this geometry is only an idealization of the irregular cell shape, simpler models are often used. In particular, the circular–cell approximation is very popular due to its low computational complexity (Petrus et al., 1998; Baltzis & Sahalos, 2005, 2009b; Goldsmith, 2005; Pirinen, 2006; Bharucha & Haas, 2008; Xiao et al., 2008; Baltzis, 2010b). Among various performance degradation factors, co-channel interference (CCI) is quite significant since the cells in cellular networks tend to become denser in order to increase system capacity (Stavroulakis, 2003). The development of models that describe CCI generates great interest at the moment. Several reliable models can be found in the

/pdf/hexagonal-vs-circular-cell-shape-a-comparative-analysis-and-2gim4vj95c.pdf

Hexagonal vs Circular Cell Shape: A Comparative Analysis and Evaluation of the Two Popular Modeling Approximations

Smart agriculture techniques have recently seen widespread interest by farmers. This is driven by several factors, which include the widespread availability of economically-priced, low-powered Internet of Things (IoT) based wireless sensors to remotely monitor and report conditions of the field, climate, and crops. This enables efficient management of resources like minimizing water requirements for irrigation and minimizing the use of toxic pesticides. Furthermore, the recent boom in Artificial Intelligence can enable farmers to deploy autonomous farming machinery and make better predictions of the future based on present and past conditions to minimize crop diseases and pest infestation. Together these two enabling technologies have revolutionized conventional agriculture practices. This survey paper provides: (a) A detailed tutorial on the available advancements in the field of smart agriculture systems through IoT technologies and AI techniques; (b) A critical review of these two available technologies and challenges in their widespread deployment; and (c) An in-depth discussion about the future trends including both technological and social, when smart agriculture systems will be widely adopted by the farmers globally. 

IoT-Equipped and AI-Enabled Next Generation Smart Agriculture: A Critical Review, Current Challenges and Future Trends

Smart agriculture techniques have recently seen widespread interest by farmers. This is driven by several factors, which include the widespread availability of economically-priced, low-powered Internet of Things (IoT) based wireless sensors to remotely monitor and report conditions of the field, climate, and crops. This enables efficient management of resources like minimizing water requirements for irrigation and minimizing the use of toxic pesticides. Furthermore, the recent boom in Artificial Intelligence can enable farmers to deploy autonomous farming machinery and make better predictions of the future based on present and past conditions to minimize crop diseases and pest infestation. Together these two enabling technologies have revolutionized conventional agriculture practices. This survey paper provides: (a) A detailed tutorial on the available advancements in the field of smart agriculture systems through IoT technologies and AI techniques; (b) A critical review of these two available technologies and challenges in their widespread deployment; and (c) An in-depth discussion about the future trends including both technological and social, when smart agriculture systems will be widely adopted by the farmers globally.

https://ieeexplore.ieee.org/ielx7/6287639/9668973/09716089.pdf

Two wireless technologies, WiMAX based on IEEE standards
and LTE standardized by 3GPP, are two competing technologies, nevertheless, are
very technically similar. This competition started with the advent of their
pre-4G versions (802.16e for Mobile WiMAX and 3GPP release 8 for LTE) and
continued with the advent of their 4G versions (WiMAX 2.0 based on IEEE 802.16 m and
LTE-Advanced standardized by Release 10). It looks that the competition ended with the
advantage of LTE. Plans are set for WiMAX to migrate/integrate with LTE in a
multiple heterogeneous access technology mode. This article addresses the
technical similarities and differences that advantage one technology over the
other technology in order to determine which of these factors might have contributed
to LTE winning. Nontechnical factors of commercial and historical nature which
might also advantage one technology over the other one are also explored.
Finally, current activities in the standardization of both WiMAX and LTE are
presented with a perspective on the prospects of both technologies.

/pdf/lte-and-wimax-comparison-and-future-perspective-1hz4vktgwz.pdf

LTE and WiMAX: Comparison and Future Perspective

With the rise of mobile and wireless technologies, more sustainable networks are necessary to support such communications. These next generation networks can now be utilized to strengthen the growing era of the Internet of Things. Powering the Internet of Things With 5G Networks is a comprehensive reference source for the latest scholarly research on the progression and design of fifth generation networks and their role in supporting the Internet of Things. Including a range of perspectives on topics such as privacy and security, large scale monitoring, and scalable architectures, this book is ideally designed for technology developers, academics, researchers, and practitioners interested in the convergence of the Internet of Things and 5G networks.

Powering the Internet of Things With 5G Networks

Telecom companies in the different generations resorted to different tools to conquer connectivity issues like coverage, throughput and quality of service. The success is driving new services of diversified requirements and more traffic which dictates a continuous increase in data rates and improved performance. This work reviews the different technology tools used to meet rates and traffic requirements of the past and the present with a look into their role in future networks. The coming fifth generation (5G), in particular, is confronted by a number of antonym challenges of capacity, spectrum, energy, connectivity, performance, complexity, and cost. Suggested tools proposed to meet these challenges and the way they act to do so are reviewed and compared to current and past solutions. The tools discussed are the use of millimetric waves, massive multiple input multiple output antenna systems, indoor–outdoor separation, ultra-dense cooperative networks, and the increased reliance on users’ terminals. The major constructional differences and tools differences between current and future 5G are finally emphasized.

Wireless Broadband Tools and Their Evolution Towards 5G Networks

4G is promising a wireless broadband with data rates up to 1Gbps. The two candidate technologies for 4G are the Advanced Long Term Evolution (Advanced LTE) which is based on the 3GPP standards and the WiMAX 2.0 based on the IEEE 802.16 family of standards. The common feature of both technologies is that they will provide All-IP connectivity with flexible bit rates and quality of service guarantees for multiple classes of services including voice, mainly using voice over IP, data and video services. Most of the performance studies of 4G technologies use highly complex and sophisticated simulations due to the multiple complexity factors in investigating 4G technologies such as All-IP flexible bit rates, adaptive coding and modulation as well as the multi-services provided. These factors usually make any modelling attempt very difficult. This paper presents a numerical/analytical model for a 4G WiMAX cell based on a multi-dimensional Continuous-Time Markov Chain (CTMC) model. Performance measures were derived for the key performance indicators such as throughput and average bit rate per cell and per service class. By assuming minimum acceptable bit rates for certain quality of service guarantees, we derived measures for blocking probabilities. The model has been formulated and solved using MOSEL-2 (Modelling Specification and Evaluation Language) which captures the key features of a 4G system that affect services at session/call level. The resuls obtained from the model using sample parameters show that, the model can provide very useful insight to system behavior and can give good first indication to the performance of such a complex system.

Performance Model of a WIMAX 2.0 All-IP 4G System

Capacity and coverage represent, in addition to QoS, the three main requirements for W-CDMA based 3G mobile communication systems. These are conflicting requirements; i.e., optimizing one will be on the account of the other two. All three, however, depend largely on the interference levels in the system. Improvements on interference are thought to have a decisive effect on the performance of the 3G system and one important interference reduction technique is the utilization of smart antennae. In this paper, we analyze capacity/coverage on the uplink in W-CDMA system utilizing switched beam smart antennae, SBSA, using a simple model of the antenna, while satisfying a certain minimum level of QoS. Limits imposed by both interference from others and the limited uplink power available to any user in the cell are considered. Results of this paper are analytical formulae for capacity/coverage that take into consideration many of the important parameters of either the antennae or the WCDMA system. A sectional view of improvement gains, if any, of either capacity or coverage upon antenna upgrading/downgrading is provided. It is shown that improvements by the directional SBSA of either capacity or coverage, are only attained at high interference conditions; i.e., higher number of users when considering coverage improvement or smaller coverage areas when considering capacity. The higher the interference conditions are the higher gain over side lobes or more beams SBSA are needed to attain improvement.

Ismat Aldmour

Papers

LTE and WiMAX: Comparison and Future Perspective

Powering the Internet of Things With 5G Networks

Wireless Broadband Tools and Their Evolution Towards 5G Networks

Performance Model of a WIMAX 2.0 All-IP 4G System

Uplink Capacity/Coverage Analysis of WCDMA with Switched Beam Smart Antennae