In this paper a novel and effective two phase admission control (TPAC) for QoS mobile ad hoc networks is proposed that satisfies the real-time traffic requirements in mobile ad hoc networks. With a limited amount of extra overhead, TPAC can avoid network congestions by a simple and precise admission control which blocks most of the overloading flow-requests in the route discovery process. When compared with previous QoS routing schemes such as QoS-aware routing protocol and CACP protocols, it is shown from system simulations that the proposed scheme can increase the system throughput and reduce both the dropping rate and the end-to-end delay. Therefore, TPAC is surely an effective QoS-guarantee protocol to provide for real-time traffic.

Intelligent transportation system (ITS) makes use of vehicle position to decrease the heavy traffic and improve service reliability of public transportation system. Many existing systems, such as global positioning system (GPS) and cellular communication systems, can be used to estimate vehicle location. The objective of wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. The non-line-of-sight (NLOS) problem is the most crucial factor that it causes large measured error. In this paper, we present a novel positioning algorithm based on genetic algorithm (GA) to locate MS when three BSs are available for location purpose. Recently, GA are widely used as many various optimization problems. The proposed algorithm utilizes the intersections of three time of arrival (TOA) circles based on GA to estimate the MS location. The simulation results show that the proposed algorithms can really improve the location accuracy, even under severe NLOS conditions.

Over a correlated flat fading channel, multiple-symbol differential detection can enhance the performance of coded differential phase shift keying (DPSK) systems but with exponential complexity. For iterative decoding schemes, the soft-input soft-output (SISO) multiple-symbol differential sphere decoding (MSDSD) can offer suboptimal performance and its complexity is quadratic with detection length. To further reduce the complexity, this paper proposes a Forward/Backward MSDSD (FB-MSDSD) for coded DPSK systems. The key idea is that the detection interval is split into two subintervals which are processed in the forward and backward directions respectively. Simulation results show that the proposed scheme has almost the same performance and lower complexity when compared with the SISO-MSDSD scheme with the same detection length.

To achieve more accurate measurements of the mobile station (MS) location, it is possible to integrate many kinds of measurements. In this paper we proposed several hybrid methods that utilized time of arrival (TOA) at seven base stations (BSs) and the angle of arrival (AOA) information at the serving BS to give location estimation of the MS in non-line-of-sight (NLOS) environments. Rather than applying the nonlinear circular lines of position (LOP), the proposed methods are easier by using linear LOP to determine the MS. In addition, the proposed methods can mitigate the NLOS effect, simply by applying the weighted sum of the intersections between different linear LOP and the AOA line, without requiring priori knowledge of NLOS error statistics. Simulation results show that the proposed methods can always yield superior performance in comparison with Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP) and the previous proposed methods employing circular LOP.

In this paper we present hybrid positioning schemes that combine time of arrival (TOA) and angle of arrival (AOA) measurements from only two base stations (BSs) to locate the mobile station (MS) in non-line-of-sight (NLOS) environments. The proposed methods utilize two TOA circles and two AOA lines to find all the possible intersections to locate the MS without requiring a priori information about the NLOS error. The commonly known Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP) have convergence problems, and the relative positioning between the MS and the BSs greatly affects the location accuracy. The resulting geometry creates a situation where small measurement errors can lead to significant errors in the estimated MS location. Simulation results show that the proposed methods always perform better than TSA and HLOP for different levels of NLOS errors, particularly when the MS/BSs have an undesirable geometric layout.

The objective of wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. When signals are propagated through non-line-of-sight (NLOS) paths, the measurements at the base stations (BSs) contain large errors which result in poor detectability of an MS by the surrounding BSs. In those situations, it is necessary to integrate all available heterogeneous measurements to improve location accuracy. This paper presents hybrid methods that combine time of arrival (TOA) at three BSs and angle of arrival (AOA) information at the serving BS to obtain a location estimate for the MS. The proposed methods mitigate the NLOS effect by using the weighted sum of the intersections between three TOA circles and the AOA line without requiring the a priori knowledge of NLOS error statistics. Numerical results show that all positioning methods offer improved estimation accuracy over those which rely on the two circles and two lines. The proposed methods always achieve better location accuracy than the Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP) do, regardless of the NLOS error statistics.

To achieve more accurate measurements of the mobile station (MS) location, it is possible to integrate many kinds of measurements. In this paper we proposed several simpler methods that utilized time of arrival (TOA) at three base stations (BSs) and the angle of arrival (AOA) information at the serving BS to give location estimation of the MS in non-line-of-sight (NLOS) environments. From the viewpoint of geometric approach, for each a TOA value measured at any BS, one can generate a circle. Rather than applying the nonlinear circular lines of position (LOP), the proposed methods are much easier by using linear LOP to determine the MS. Numerical results demonstrate that the calculation time of using linear LOP is much less than employing circular LOP. Although the location precision of using linear LOP is only reduced slightly. However, the proposed efficient methods by using linear LOP can still provide precise solution of MS location and reduce the computational effort greatly. In addition, the proposed methods with less effort can mitigate the NLOS effect, simply by applying the weighted sum of the intersections between different linear LOP and the AOA line, without requiring priori knowledge of NLOS error statistics. Simulation results show that the proposed methods can always yield superior performance in comparison with Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).