A handover algorithm for broadband wireless access system on railway

Using a part of a general methodology for population analysis, developed recently in Lazov and Lazov [1], and relying on the fundamental concepts of system information i and system entropy $$S=E\left( i \right) $$S=Ei, this paper promotes a methodology for information and capacity analysis of broadband wireless access (BWA) systems. A BWA system consists of a base station (BS) and a group of M users in its coverage area, with N simultaneously active users, $$0\le N\le M$$0≤N≤M, working in point-to-multipoint mode. As in [1], we model this system as family of birth-death processes (BDPs), with size $$M+1$$M+1, in equilibrium, indexed by the system utilization parameter $$\rho $$ź, ratio of its primary birth and death rates, $$\rho =\lambda /\mu $$ź=ź/μ. We evaluate the BWA system information and entropy, and full system capacity, and then, assuming the same Gaussian distribution for the arrival traffic at BS from any user, system capacity (as a function of the system information) and its mean value, and mean normalized square deviation of the system capacity from its linear part. We compare the information of empty $$\left( {N=0} \right) $$N=0 and full $$\left( {N=M} \right) $$N=M system with system entropy, and further, system mean capacity with full system capacity, as functions of parameter $$\rho $$ź. The developed methodology is illustrated on families of BDPs with truncated geometrical, truncated Poisson and Binomial distributions as their equilibrium ones, which model the information linear, Erlang loss and Binomial BWA systems, respectively.

In IEEE 802.16 broadband wireless access (BWA) systems, the uplink performance is affected by the size of the contention period in the subframe since the bandwidth request (BR) messages are sent during the period and the bandwidth for each service can be allocated only when the BR messages are accepted. In this paper, we develop a cross-layer analytical model for designing the optimal size of the contention period in IEEE 802.16 BWA systems with various classes of services. The model is validated by Monte Carlo simulation, and the results show that our cross-layer design provides a good scheme for determining the contention period size when the system performance is optimized.

A fair and efficient service flow management architecture for IEEE802.16 broadband wireless access (BWA) systems is proposed for TDD mode. Compared with the traditional fixed bandwidth allocation, the proposed architecture adjusts uplink and downlink bandwidth dynamically to achieve higher throughput for unbalanced traffic. A deficit fair priority queue scheduling algorithm is deployed to serve different types of service flows in both uplink and downlink, which provides more fairness to the system. Simulation results show the proposed architecture can meet the QoS requirement in terms of bandwidth and fairness for all types of traffic.

Mobile WiMAX is a broadband technology that is capable of delivering triple play services (voice, data, and video). However, mobility in mobile WiMAX system is still an issue when the mobile station (MS) moves and its connection is handed over between base stations (BSs). In the handover process, scanning is one of the required phases to find the target BS. During the handover scanning process, the MS must synchronize with all the advertised neighbour BSs (nBSs) to select the best BS candidate for the incoming handover action. Without terminating the connection between the SBS and MS, the SBS will schedule the scanning intervals and sleep-intervals (also called interleaving interval) to MS for the handover scanning. However, during the scanning interval period, all the coming transmissions will be paused. Therefore, the redundant or unnecessary scanning of neighbouring BS cause delay and MAC overhead which may affect real-time applications. In this paper, the MS movement direction prediction (MMDP) based handover scanning scheme is introduced to overcome the mobile WiMAX handover scanning issue. It based on dividing the BS coverage area is into zones and sectors. According to the signal quality; there are three zones, no handover (No-HO), low handover (Low-HO) and high handover (High-HO) zones respectively and six sectors. In this scheme, only two BSs can become candidates; the two that the MS moves toward them will be chosen as the candidate for the handover scanning purpose. Hence, the handover scanning process repetition will be reduced with these two shortlisted BS candidates instead of scanning all nBSs. Thus, MMDP will reduce scanning delay and the number of exchange messages during the handover scanning comparing to the conventional scanning scheme. Although, the MMDP may need an extra computational time, the prediction and scanning process will be finished before the MS reach the High-HO zone, which mean the end-user's running application will be affected. Simulation results show that the proposed MMDP scheme reduces the total handover scanning delay and scanning interval duration by 25 and 50 % respectively. Also, the size of scanning message is reduced, which leads to reduced signalling overhead.

Many handover algorithms are proposed in the literature. However, to make a better handover and keep the QoS in wireless networks is very difficult. In this paper, we propose a new handover system based on fuzzy logic. The proposed system uses 3 parameters for handoff decision: the change of signal strength of the present Base Station (BS), signal strength from the neighbor BS, and the distance between Mobile Station (MS) and BS. The performance evaluation via simulations shows that proposed system can avoid ping-pong effect and has a good handover decision.

Nowadays, one of the most important challenges in heterogeneous networks is the connection consistency between the mobile station and the base stations. Furthermore, along the roaming process between the mobile station and the base station, the system performance degrades significantly due to the interferences from neighboring base stations, handovers to inaccurate base station and inappropriate technology selection. In this paper, several algorithms are proposed to improve mobile station performance and seamless mobility across the long-term evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX) technologies, along with a minimum number of redundant handovers. Firstly, the enhanced global positioning system (GPS) and the novel received signal strength (RSS) prediction approaches are suggested to predict the target base station accurately. Then, the multiple criteria with two thresholds algorithm is proposed to prioritize the selection between LTE and WiMAX as the target technology. In addition, this study also covers the intercell and cochannel interference reduction by adjusting the frequency reuse ratio 3 (FRR3) to work with LTE and WiMAX. The obtained results demonstrate high next base station prediction efficiency and high accuracy for both horizontal and vertical handovers. Moreover, the received signal strength is kept at levels higher than the threshold, while maintaining low connection cost and delay within acceptable levels. In order to highlight the combination of the proposed algorithms' performance, it is compared with the existing RSS and multiple criteria handover decision algorithms.

Orthogonal frequency division multiplexing (OFDM) has been widely regarded as an effective modulation technique for mitigating the effects of ISI in a frequency selective fading channel and for providing reliable high data rate transmission over wireless links. Adaptive antenna arrays at the base and mobile stations can achieve further increases in system's capacity and bandwidth efficiency, as well as in QoS improvement in conventional OFDM systems. The conventional adaptive antenna arrays based OFDM systems always use the sub-carriers characterized by the first largest eigenvalues to transmit the OFDM block symbols. In this paper and in contrast to previous work, we propose dynamic sub-channel allocation with adaptive beamforming for broadband OFDM wireless transmission systems. The proposed system adaptively selects the eigenvectors associated with the relatively large sub-channel eigenvalues to generate the beamforming weights at the mobile and base stations and then dynamically assigns the corresponding best sub-channels to transmit the OFDM block symbols. It is shown by simulation that, without adding much complexity, the proposed system can achieve a better performance than an adaptive antenna arrays based OFDM system without dynamic sub-channel allocation over multipath fading channels. Simulation results also reveal that the proposed system is not too sensitive to channel estimation errors.

As for radio channel control of a cellular mobile communication system, location measurement is an important technique for determining the base station to be Connected with the mobile station. This paper describes the radio zone selection characteristic when a part of the control channel is time‐shared by base stations and the reception level of each base station is measured at mobile stations. MSSC (Multitransmitter Simul/Sequential Casting) of control channels is proposed, which improves the location measurement and is suitable for a high‐capacity system. The MSSC channel consists of simul‐cast parts and sequential‐cast parts. Its speech connection control sequence when applied to the cellular mobile communication system is shown. Next, the relation between the reception level variation characteristic in land mobile communication and the average reception level measurement accuracy when burst signals are received several times is studied. Both analytical results and laboratory experimental simulation results are shown. Finally, the zone selecting rate of a mobile station is calculated and the effect of the proposed control channel configuration is clarified.

<p>WiFi networks based on the IEEE 802.11 standard are widely used indoors or outdoors as simple and cost-effective wireless technology. However, the data connection is significantly disrupted when mobile stations (STAs) switch between access points (APs). Furthermore, high packet loss occurs during the switching period. Therefore, mobility is a critical issue that needs to be solved in WiFi networks. In cellular networks, handover is used to keep ongoing data transfer when network clients switch between base stations. However, the handover algorithm is not supported in the 802.11 standard for WiFi networks. Self-Organizing Network (SON) functionality enables seamless handover in cellular networks, improving network performance. However, the SON functionality has not been fully researched in WiFi networks, especially for mobility management. Motivated by the SON functionalities, a SON approach is proposed to automatically optimize the handover algorithms for WiFi networks. This approach focuses on the SON functionalities including self-configuration, self-optimization and self-healing using machine learning techniques to develop new algorithms for WiFi mobility management. The overall goal of this thesis is to optimize handover performance as well as enhance the network’s capabilities.</p>

The Internet protocol (IP) can potentially become the universal network-layer protocol over all wireless systems as it already is for wireline packet networks. Such an all-IP wireless and wireline network can bring the proven advantages of IP networking to mobile users. However, realizing an all-IP wireless network introduces many challenges, among which is soft handoff. Two major problems need to be solved in order to support soft handoff. First, multiple streams of the same IP traffic have to be distributed via multiple base stations to a mobile station. Second, pieces of data arriving at the mobile station at the same time from different base stations need to be copies of the same data in order for the mobile station's radio system to correctly combine these different pieces into a single copy. A similar problem also needs to be resolved in the reverse direction from mobile stations to base stations. Solving these problems in a distributed all-IP wireless network remains a challenge. Although solutions exist for today's circuit-switched wireless systems. This article presents a new approach for soft handoff in distributed all-IP wireless networks. It consists of two main parts. First, a new design of IP-based distributed base stations enables mobile stations in multiple cells to be on the same IP subnet and multiple streams of the same data to be distributed via multiple base stations to a mobile without broadcasting/multicasting and with minimal signaling. Second, a novel IP-layer procedure performed by the base stations ensures that the data coming simultaneously from multiple base stations to a mobile station are copies of the same data.

The IEEE 802.16e-2005 standard for broadband wireless access provides a rich quality of service (QoS) framework suitable for supporting a multitude of services. In IEEE 802.16e, the uplink resource allocation is based on a request-grant mechanism where a mobile stations (MS) requests allocations of transmission opportunities from the base station (BS). Every frame, the BS decides the amount of resources to be granted for each uplink connection according to its QoS parameters. While the grant is decided on a connection basis, the BS aggregates the grants allocated for all connections of each MS and adds a single entry for each MS in the allocation MAP message. Two main challenges exist for scheduling at the MS side: the first is how to divide the grant among the connections according to their declared QoS parameters and requested bandwidth and the second is to be able to perform this operation prior to the arrival of the subsequent allocation from the BS. In this paper, we describe a new efficient scheme for mobile station uplink scheduling that meets these challenges. The scheme is a hierarchical credit-based algorithm based on the deficit round robin method. The algorithm is designed to prevent bandwidth stealing and starvation of low-priority connections. We provide simulation results that show the excellent performance of the scheme even under extreme overload conditions. The results show the isolation of service classes and the stability of the scheme.

The massive growth of data consumption and the variety of wireless technology emergence has made the handover (HO) an attractive research topic nowadays, mainly due to the popularity of Wireless Local Area Networks (WLANs), which allow users to reach high-speed data communication while they are in movement. Moreover, mobile devices such as tablets and smartphones have also become increasingly popular due to their low cost and ease of use, and an increase in mobile device use is expected to accelerate in the coming years, along with the availability and use of applications such as real-time services and online gaming. The traditional HO methods will likely not meet the requirements of mobile devices for modern applications due to the lack of intelligence, lack of awareness Quality of Service (QoS) and Quality of Experience (QoE) requirements of mobile users. We, therefore, introduce a novel architecture that supports horizontal HO in homogenous networks. This architecture is based on the Software-Defined Wireless Networking (SDWN) concept, where the wireless network is controlled centrally and the wireless Access Points (APs) are programmable. In this architecture, HO algorithms will assist wireless users to find the network that could best support the application requirements through Quality of Service (QoS) and Quality of Experience (QoE) management policies. The first HO algorithm proposed in this thesis is called Quality of Experience Oriented Handover Algorithm. This algorithm will guarantee the best possible connectivity to the users in terms of their QoE and QoS requirements and outperforms the traditional methods in a sparse network environment. The second contribution is called Optimised Handover Algorithm for Dense WLAN Environments. This algorithm has been designed to address dense network environments via taking into consideration the Adaptive Hysteresis Value (AHV). The AHV will help the Optimised Handover Algorithm via reducing the so-called ping-pong effect. This contribution shows promising performance results by selecting the best candidate AP, decreasing the number of redundant HO and avoiding the ping-pong effect. The final contribution is called Priority Based Handover Algorithm. We extended our proposed SDWN architecture in order to include the concept of prioritising users and make a smart decision during the process of HO. This algorithm will prioritise a certain class of users to avoid the effect of the over-congestion. The results show that the approach based on priority outperforms the state of the art and provides better QoE to the high priority users despite the over-congestion situation.

In a cellular communication system, deploying a relay station (RS) is an effective alternative to installing a new base station (BS). A dual-hop network enhances the throughput of mobile stations (MSs) located in shadow areas or at cell edges by installing RSs between BSs and MSs. Because additional radio resources should be allocated to the wireless link between BS and RS, a frame to be transmitted from BS is divided into an access zone (AZ) and a relay zone (RZ). BS and RS communicate with each other through the RZ, and they communicate with their registered MSs through an AZ. However, if too many MSs are registered with a certain BS or RS, MS overloading may cause performance degradation. To prevent such performance degradation, it is very important to find the proper positions for RSs to be deployed. In this paper, we propose a method for finding the sub-optimal RS deployment location for the purpose of load-balancing and throughput enhancement. The advantage of the proposed method is the efficiency in find the sub-optimal location of RSs and its reliable tradeoff between load-balancing throughput enhancement. Since the proposed scheme finds the proper position by adjusting the distance and angle of RSs, its computational complexity lower than other global optimization approach or learning-based approach. In addition, the proposed scheme is constituted with the two stages of load-balancing and throughput enhancement. These procedures result in the appropriate tradeoff between load-balancing and throughput enhancement. The simulation results support these advancements of the proposed scheme.

In Mobile WiMAX, a Base Station (BS) delivers security keys to Mobile Stations (MSs) through a key distribution scheme to guarantee security and access control. The MSs need to perform ciphering operations to access the keys upon rekeying process. In this way, the MSs consume energy to receive and decrypt the keys for further communication with a BS, while the BS consumes energy to encrypt and transmit the keys. In current key distribution schemes, any member join or leave event results in a key updating, and the duration of the MSs stay in the cell is not important, but on average low speed MSs tend to stay longer in the cell, while fast MSs will leave the cell faster. This paper proposes an Efficient Key Distribution scheme to decrease the number of exchanged keys which results in minimizing energy consumption of the network by grouping the MSs into the different subgroups based on their speeds using complete binary tree. Analysis shows that the proposed scheme reduces energy consumption during key updating process.

Cell selection is the process of determining the cell(s) that provide service to each mobile station. Optimizing these processes is an important step toward maximizing the utilization of current and future cellular networks. We study the potential benefit of global cell selection versus the current local mobile SNR-based decision protocol. In particular, we study the new possibility available in OFDMA-based systems, such as IEEE 802.16m and LTE-Advanced, of satisfying the minimal demand of a mobile station simultaneously by more than one base station. We formalize the problem as an optimization problem, and show that in the general case this problem is not only NP-hard but also cannot be approximated within any reasonable factor. In contrast, under the very practical assumption that the maximum required bandwidth of a single mobile station is at most an r-fraction of the capacity of a base station, we present two different algorithms for cell selection. The first algorithm produces a (1-r)-approximate solution, where a mobile station can be covered simultaneously by more than one base station. The second algorithm produces a 1-r/2-r-approximate solution, while every mobile station is covered by at most one base station. We complete our study by an extensive simulation study demonstrating the benefits of using our algorithms in high-loaded capacity-constrained future 4G networks, compared to currently used methods. Specifically, our algorithms obtain up to 20 percent better usage of the network's capacity, in comparison with the current cell selection algorithms.