Propagation path losses affecting intervehicle communication (IVC) at 60 GHz are presented. In order to examine the radio-propagation characteristics in the IVC system, in the first stage of our investigation, we have carried out propagation tests between two vehicles communicating in a line-of-sight (LOS) situation at fixed positions on a smooth surface paved with asphalt, which is the normal communication condition. Furthermore, the non-LOS (NLOS) situation with up to three intermediate vehicles, which can cause an obstruction, has been conducted. To construct path-loss models in NLOS cases, the uniform theory of diffraction technique was applied to the calculation of waves propagating through the intermediate vehicles. The propagation path models were derived from the measured results. In the second stage, a path-loss prediction formula was derived by statistically processing the data that had been calculated using the propagation path model. The propagation tests between the vehicles in motion confirm that the path-loss prediction formula is very useful when the communicating vehicles are moving, and it is therefore suitable for designing the cells that form the IVC.

Recently, inter-vehicle communication systems based on the multi-hop ad-hoc wireless communication systems have been discussed in the field of ITS telecommunications, disaster management communications and so on. In this paper, we report and discuss about the examination of physical layer of multi-hop ad-hoc inter-vehicle wireless communication system which has been newly developed for multiple purposes, especially for the disaster management. We aim at the multi-hop communications system for disaster which used the disaster prevention using a VHF band from such a background. For starting the development of the ad-hoc communications system, for example, the possibility in existing communications systems, such as 802.11, etc. is taken into consideration. We examined various system simulations, about each class of the physical layer, the MAC section and a network layer. To get the optimal solution, examination was performed from the stage of a basic system design, the equipment trial production was performed after checking the validity for the practicality check in the field. This paper describes especially the outline of the simulation result of having followed the MAC section which is one of the fundamental components of this system as basic examination of an equipment trial production, and the physical layer portion.

Access security is an indispensable component in the future generation wireless networks to enable the trusted communications. During the User Equipment (UE) access procedure, the authentication overhead analysis is able to provide insights in understanding the security management performance. To unify the model for analyzing the authentication traffics under different location management schemes, we introduce the concept location update inter-arrival time. Furthermore, based on the UE's typical behavior, we propose a system model and define the metric number of User Authentication Request (UAR) in SGSN residence time to evaluate the authentication cost. Numerical results are illustrated to show the interaction between the parameters and the performance metrics. The sensitivity of call arrival process and the effects of location management schemes are also discussed. Copyright © 2006 John Wiley & Sons, Ltd.

In the literature, there are two common assumptions for the tele-traffic parameter in analyzing the wireless network performance, that is, the tele-parameter follows a specific probability density function (pdf) and additionally the pdf exists closed-form Laplace Transform (LT). However, taking into account the cell irregular shape, the specific pdf may be unavailable while only the measured statistical moments are available. Moreover, the pdf function may not exist a closed-form LT, for example, lognormal distribution function. In this paper, based on the Central Limit Theorem and hyper-Erlang universal approximation property, we propose an approximation method applicable in the situations when only the statistical moments are available or LT of pdf does not exist. We then employ the technique in diverse applications, including the performance analysis of wireless network and the cost evaluation of mobility management. Extensive numerical examples demonstrate the good approximation capability to the exact formula and the simulation results. Copyright © 2006 John Wiley & Sons, Ltd.

Mesh WiMAX is a very good candidate for Maritime Intelligent Transport System (ITS) characterized by the long distance and multiple hops communication. In Maritime ITS, handover would be an important issue affecting the performance of the whole network. Current mobile WiMAX does not support multi-hops handover. This paper presents a novel multi-hops, soft handover solution for Mesh WiMAX network in Maritime ITS. The simulation shows that with this soft handover, network throughput has been improved significantly.

We propose and study the location management congestion problem arising in the group mobility scenarios. In the hot-spot locations, e.g., supermarket, bus interchange, or public transportation systems, a large number of travelers move into the same area concurrently and trigger the location update (LU) procedure simultaneously to register their new locations. However, due to the limited bandwidth in a base station, only a small part of the LU requests has the opportunity to capture a radio channel and succeeds in refreshing the new information to the corresponding database in the wireless networks. The remaining mobile terminals (MTs) are unable to obtain a radio channel, and consequently, the LU requests are rejected. A significant consequence of a failed LU is the out-of-date location identity in the network databases and, thereafter, the incapability in establishing the valid route for the potential call connection request, which will seriously degrade the network quality-of-service (QoS). We develop a queueing model to characterize the congestion issue and propose a buffer scheme to eliminate this problem. The consequence of the LU failure on the MT's call activity is also investigated. The comparison demonstrates the high efficiency of the proposed approach in decreasing the LU failure as well as the resulting call blocking probability. The analytical model has been validated by the discrete event simulation

The call completion characteristics in wireless networks with the presence of an inherently lossy wireless link are presented in this paper. The closed-form formula for the significant performance metric in terms of the call completion probability is developed under the generalized wireless channel model and the general call holding time distribution based on the complex theory and transform techniques (Laplace-Stieltjes transform and z transform). The particular results under the typical wireless channel model and the commonly used call holding time are presented. In order to reflect the unique characteristics of the wireless channel erroneous state, we further introduce the resource occupancy time per call and the completed call holding time per call and present their properties in terms of probability density function and statistical moments. The comparison indicates that different call holding time distributions may lead to a substantial discrepancy. The effects of the first-order as well as second-order statistical moments of the call holding time and the wireless channel state duration upon the performance metrics are discussed

This document provides a submission that describes a seaport radio path loss model suitable for fixed wireless applications. Purpose This is for use by the Relay Task Group to evaluate air interface performance Notice This document has been prepared to assist IEEE 802.16. It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein. Release The contributor grants a free, irrevocable license to the IEEE to incorporate material contained in this contribution, and any modifications thereof, in the creation of an IEEE Standards publication; to copyright in the IEEE’s name any IEEE Standards publication even though it may include portions of this contribution; and at the IEEE’s sole discretion to permit others to reproduce in whole or in part the resulting IEEE Standards publication. The contributor also acknowledges and accepts that this contribution may be made public by IEEE 802.16. Patent Policy and Procedures The contributor is familiar with the IEEE 802.16 Patent Policy and Procedures <http://ieee802.org/16/ipr/patents/policy.html>, including the statement "IEEE standards may include the known use of patent(s), including patent applications, provided the IEEE receives assurance from the patent holder or applicant with respect to patents essential for compliance with both mandatory and optional portions of the standard." Early disclosure to the Working Group of patent information that might be relevant to the standard is essential to reduce the possibility for delays in the development process and increase the likelihood that the draft publication will be approved for publication. Please notify the Chair <mailto:chair@wirelessman.org> as early as possible, in written or electronic form, if patented technology (or technology under patent application) might be incorporated into a draft standard being developed within the IEEE 802.16 Working Group. The Chair will disclose this notification via the IEEE 802.16 web site <http://ieee802.org/16/ipr/patents/notices>. 2006-04-29 IEEE C802.16j-06/003 1 Seaport Path Loss Model for Fixed Wireless Applications Ming-Tuo Zhou, Yan Zhang, V.D. Hoang, Masayuki Fujise, J. Shankar, and Hai-Guang Wang : Wireless Communications Laboratory, National Institute of Information and Communications Technology : Institute for Infocomm Research, Singapore Introduction Due to the rapid development of the Internet, more and more users in anchored or moving ships in seaports hope to access broadband IP services. Although the users may access the Internet services via the GPRS or satellite links, the access is normally limited due to the small bandwidth or the limited channels available. WiMAX can be a good candidate to provide broadband services to the ship users since the Fixed Wireless Applications has potential data rate of several Mbps or several tens Mbps and a relatively long cell radius of tens kilometers [1]. In order to build an IEEE802.16 network to provide broadband services to the seaport users, a wireless channel model in seaport environments is necessary for evaluation of the air interface performance of the Fixed Wireless Applications. However, to the knowledge of the authors so far, the channel models for Fixed Wireless Applications previously proposed to the IEEE 802.16 Task Group just include models in urban and suburban environments [2]; a path loss model for Fixed Wireless Application in seaport environments cannot be fund in current available IEEE802.16 documents. In this document, we propose an empirical seaport path loss model for the Fixed Wireless Applications. This document is to fill the above mentioned blank and to serve as a supplement to the path loss models in urban and suburban land environments proposed in [2]. The Proposed Seaport Path Loss Model The seaport path loss model proposed in this document is given by ( ) 0 10 log10 f PL A d d s PL γ = + + + ∆ [dB] for d>d0, (1) where ♦ ( ) 0 20log10 4 A d π λ = ( λ is the wavelength in m), d0=100 m, d is the Tx-Rx distance in m ♦ b b a b h c h γ = − × + , a=2.358, b=0.00145, and c=0.45, hb is the base antenna height between 4 m to 185 m ♦ s is a zero mean Gaussian variable with standard deviation b b l m h n h σ = − × + [dB], l=7.6, m=0.35, and n=6.4, hb is between 4 m to 185 m ♦ ∆PLf =6log10( f /5800), f is frequency in MHz The path loss above means, PL = Pt+G-Pr [dB], where Pt is the transmitter power in dBm, G (dB) includes the effect of antenna gain and the cable loss, and Pr is the mean received power in dBm. Testing Environment and Data Collection Method The path loss measurement is carried out in Singapore Port, which is one of the busiest ports in the world. It has a typical seaport environment with many ships anchored or moving in the port as shown in Fig. 1 [3]. The sea wave height in good weather condition is about 1 m. Due to the sea environment, the radio channel properties of the seaport are different from the urban and the suburban environments and it is necessary to be studied for evaluation of the performance of the Fixed Wireless Applications specially. 2006-04-29 IEEE C802.16j-06/003 2 The testing configuration diagram is schematically shown in Fig. 2. The transmitter was fixed on the shore or on the top of a tall building. The receiver is amounted on a ship. During the measurements, the receiver ship stops on different locations to change the transmitter-receiver distance. GPS is used to keep track of the separation distance between the transmitter and receiver. As the transmitter is at a fixed location in one measurement scenario, only the receiver is required to read the GPS position. In the test, the GPS is read every second by a laptop and time-stamped automatically. In the measurement, the separation between the transmitter and the receiver can be far as 18 km. Three experiment scenarios were implemented: two in east side of the Singapore Port and one in the West Coast of the Singapore Port. In the three experiments, the base station antenna heights are 4 m, 76 m and 185 m (to the mean sea surface), respectively. The receiver antenna height is about 8 m (to the mean sea surface). The base station antenna and the receiver antenna are both omni directional. The radio-frequency of the continue wave (CW) in measurements is 5.8 GHz. The receiver antenna is connected to a spectrum analyzer. For continuous data acquisition, the spectrum is connected through Ethernet cable to a laptop. The laptop will record peak power reading from the spectrum analyzer with the laptop’s timestamp. The measured data are averaged every 30 seconds to average the fast local fading due to multipath. In addition the roll of the receiver ship can provide spatial averaging of the fast local fading in some degree. Process Building the Seaport Path Loss A general path loss model is used in building the seaport path loss model similarly to the method used in [4]. The general path loss model is given by ( ) 0 10log10 PL A d d s = + + for d>d0, (2) where d0 is the close-in reference distance [2], [4], ( ) 0 20log10 4 A d π λ = ( λ is the wavelength in m) is the path loss at the reference distance d0, and s is a zero-mean Gaussian variable with standard deviation σ describing the shadowing effect [4]. By setting a typical reference distance for macrocell d0=100 m [2], the scatter plot for the cases with base station antenna heights 4 m, 76 m and 185 m are shown in Fig. 3, Fig. 4 and Fig. 5, respectively. The blue points in the three figures are the averaged path loss, and the read lines are the linear regression results with Minimum Mean Square Error (MMSE) constraint for the measured data. In Table I, the analyzed path loss exponent γ and the standard deviation σ are listed. Table I. Results of the linear regression with MMSE constraint for seaport path loss measurements. Base antenna height (m) 4 76 185 γ 2.462 2.259 2.090 σ 10.084 5.111 3.362 2006-04-29 IEEE C802.16j-06/003 3 By curve fitting as shown in Fig. 6, the change of the path loss exponent measured with the antenna height hb is given by b b a b h c h γ = − × + , (3) where a=2.358, b=0.00145, and c=0.45, and the hb is between 4 m to 185 m. Similarly, the curve fitting of the standard deviation of s to the antenna height is shown in Fig. 7, and is given by b b l m h n h σ = − × + [dB], (4) where l=7.6, m=0.35, and n=6.4, hb is between 4 m to 185 m. Since our measurements were carried out at 5.8 GHz, the path loss in seaport environment is needed to be corrected if applied to other close frequencies [5]. When a typical value of α =0.6 is used, where α is the parameter describing the path loss changes with frequency by 2 f α + [5], the frequency correction term is given by ∆PLf =6log10( f /5800) [dB], (5) where f is the frequency in MHz. The parameter α may deviates from 0.6 depending on the detailed environment [5]. References [1] IEEE Standard for Local and Metropolitan area networks, Part 16: Air Interference for Fixed Broadband Wireless Access Systems, IEEE 802.16-2004 [2] V. Erceg, et.al, “Channel Models for Fixed Wireless Applications,” IEEE 802.16a-03/01 [3] http://www.geog.umontreal.ca/Geotrans/fr/ch5fr/conc5fr/singportfr.html [4] V. Erceg., et.al, “An empirically based path loss model for wireless channels in suburban environments,” IEEE JSAC, vol. 17, no. 7, July 1999, pp. 1205-1211. [5] T.-S. Chu and L.J. Greenstein, “A quantification of link budget differences between the cellular and PCS bands,” IEEE Trans. Veh. Technol., vol. 48, no. 1, Jan. 1999, pp. 60-65. 2006-04-29 IEEE C802.16j-06/003 4 Fig. 1. A view of the Singapore Port [3]. Fig. 2 Schematic diagram of radio path loss measurement in seaport environments. 2006-04-29 IEEE C802.16j-06/003 5 Fig. 3 Scatter plot for path loss measurement at frequency 5.8 GHz in the Singa

In this paper, the study of millimeter-wave frequency synthesizer over the world is overviewed in detail. The recent achievements obtained in 60GHz frequency synthesizer development are reported. Some kinds of 60GHz frequency synthesizer schemes are analyzed mainly on its advantages and drawbacks. The suggestions to develop millimeter synthesizer are also given in the paper.

There are two major contributions in this paper. The first is to exam the Poisson assumption for the authentication traffic process triggered by the location update (LU) requests. For this, we develop an analytical model and efficient, recursive algorithm to derive the LU inter-arrival time in static as well as dynamic location management scheme. The analysis is validated by simulation and the numerical investigation indicates that the Poisson process is invalid in approximating the authentication requests. The second goal is to investigate the issue: whether different mobility management schemes have a significant effect on the authentication traffic evaluation. To answer this, we propose a system model to incorporate different LU policies. Via simulation, we evaluate the authentication traffics under static and dynamic location management schemes. The comparison demonstrates that, due to the diverse network architecture as well as the different event triggering LU message, there are significant discrepancy in generating authentication traffic load. The result reveals the fact that the performance of security management and the mobility management in wireless mobile networks interact with each other.