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# An accelerating handover process scheme for IEEE 802.16j multi-hop relay networks

- Jau-Yang Chang
^{1}Email author

**2013**:45

https://doi.org/10.1186/1687-1499-2013-45

© Chang; licensee Springer. 2013

**Received:**30 June 2012**Accepted:**31 January 2013**Published:**21 February 2013

## Abstract

IEEE 802.16j multi-hop relay network systems provide the mobile wireless communication environment. In such network systems, the handover scanning procedure allows a mobile station (MS) to obtain the information about the handover target base stations (BSs) or relay stations (RSs). The network systems need more time to negotiate the association parameters and to handle scanning the BSs and the RSs when the number of BS and RS increases. It results in more overhead for the handover scanning procedure. In order to accelerate the handover process and reduce the transmission interruption, efficient handover scanning procedure schemes and corresponding algorithms must be developed and designed. A novel relative angle computing algorithm is proposed in this article to accelerate the handover process by taking into account the moving behavior of the MS, and the distances among the MS, the RS, and the BS. The main idea of this algorithm is to reduce the management information overhead and to estimate the potential moving path of the MS in the wireless mobile communication networks. By using the proposed scheme, we eliminate the unnecessary associations and scanning intervals, and reduce the handover scanning procedure efficiently. Simulation result demonstrate the superior performance of our proposed scheme and its ability to strike the appropriate performance in the handover overhead and the message delay for IEEE 802.16j multi-hop relay network systems.

## Keywords

- Base station, Handover
- IEEE 802.16j
- Message delay
- Mobile station
- Relay station

## 1. Introduction

IEEE 802.16 Broadband Wireless Access Systems, also refereed as WiMax (Worldwide Interoperability of Microwave Access), is designed to evolve as a suite of air interface for fixed, portable, and mobile wireless access systems. This standard is a promising technology to support high transmission rate and predefined quality-of-service (QoS) framework in the broadband wireless networks. This technology can provide a cost-effective broadband access solution to use for connecting local area networks to the Internet and to support mobile applications such as fourth generation mobile systems [1].

Several researches on the relay issues have been conducted in IEEE 802.16j multi-hop relay network systems. With respect to the relay selection issues, Ann et al. [3] propose a path selection method considering the link available bandwidth, signal-to-noise ratio (SNR), and hop count in non-transparent mode of IEEE 802.16j. This scheme only suggests a suitable path for the new RSs and it does not consider the mobile environment for the MSs. Ge et al. [4, 5] analyze the relay selection in IEEE 802.16j multi-hop relay vehicular networks. An analytical model is developed in this article for locating and selecting the RS based on the locations of MSs. These two articles only consider a transport system with the highway mobility pattern. An effective path selection metric for IEEE 802.16j multi-hop relay networks is proposed in [6] to improve the network throughput. The authors use an effective radio resource index to calculate the cost function and determine the relay path between the BS and the MS. Shih et al. [7] propose a high spectral efficiency and load-aware metric for the path selection in IEEE 802.16j multi-hop relay networks. A comprising function is developed in this article to formulate the path cost to evaluate the possible relay paths and improve the network throughput. Previous schemes described above do not take into account the problem in the handover process with respect to QoS guarantees for the MSs in an IEEE 802.16j multi-hop relay network. These previously developed schemes ignore the discussion of the handover overhead and message delay for an MS. They only emphasize the network throughput enhancement.

Several handover techniques have been proposed to support QoS provisioning in IEEE 802.16-based systems. With regard to the handover issues in IEEE 802.16e network systems, analytical models have been proposed in [8–13], which have been validated to some extent through simulations. Nevertheless, only a few research articles have studied handover issues in IEEE 802.16j network systems. A reducing inter-cell handover events (RIHE) based on cell id information in multi-hop relay system is proposed in [14] to decrease handover signaling overhead, latency, and unnecessary handovers. The authors propose a handover method that reduces inter-cell handover but increases intra-cell handover events by modifying the BSID format into the hierarchical BS/RS ID. Becvar et al. [15] propose an optimal handover scanning procedure (OHSP) in IEEE 802.16j network systems to reduce the management information overhead and to maximize the user data throughput. The modification of scanning procedure is based on the uplink direction by adding identification addresses of all recommended stations for scanning into one scanning request message. In [16], this article presents handover schemes in multi-hop cellular networks (HSMCN) where RSs are located either inside a cell or on the boundary between two adjacent cells. By deploying RSs on the boundary between two adjacent cells, the service-interruption time caused by inter-cell handover is reduced. Yun et al. [17] propose a fast handover scheme (FHS) to reduce the handover signaling cost and to decrease handover delay by applying fast handovers for mobile IPv6 (FMIPv6) to IEEE 802.16j networks, which determines the cross-subnet handover in advance through the interaction of MAC layer messages. Sultan et al. [18] perform simulation study of three handover techniques (SSTHT) within the IEEE 802.16j standards and prove that the macro diversity handover (MDHO) outperforms the HHO and fast base station switching. MDHO is the process by which an MS maintains connection with two or more access stations called a diversity set. In [19], a topology-aware macro diversity handover technique (TMDHT) is proposed to improve the conventional MDHO.

These previously developed schemes [15–17] described above do not take into account the moving situation of MSs. Due to users’ mobility and insufficient bandwidth in the mobile wireless networks, it is important to provide QoS guarantees such as the message delay for an MS in IEEE 802.16j systems. From the point of view of mobile user, the message delay is obviously undesirable and very inconvenient, so the mobile users are not tolerant of this problem. Unsatisfied mobile users may change to the competing system. Hence, it is important to accelerate the handover process in IEEE 802.16j multi-hop relay networks. The message delay becomes the most significant QoS factor in such networks. Therefore, the performance parameters of interest in this article are the handover overhead and the message delay.

**Comparison of the handover methods proposed in the IEEE 802**.**16j systems**

The rest of this article is organized as follows. In Section 2, we present the system model of IEEE 802.16j multi-hop relay networks. In Section 3, we illustrate the proposed scheme in detail. In Section 4, we present our simulation model and analyze the comparative evaluation results of the proposed scheme through the simulations. Finally, some conclusions are given in Section 5.

## 2. System model

*P*

_{ t }is the transmission power,

*P*

_{ n }is the thermal noise power,

*f*is the center frequency,

*c*is the speed of light, and

*d*is the distance between two communication nodes. The SNR value can be obtained in the RSS measurement phase in order to determine the handover execution. The distance between two communication nodes can be calculated based on the SNR value.

**Transmission model**

Modulation | Coding rate | Receiver SNR (dB) | Data rate (Mbps) | Distance (km) |
---|---|---|---|---|

BPSK | 1/2 | 3.0 | 1.269 | 3.2 |

QPSK | 1/2 | 6.0 | 2.538 | 2.7 |

QPSK | 3/4 | 8.5 | 3.816 | 2.5 |

16-QAM | 1/2 | 11.5 | 5.085 | 1.9 |

16-QAM | 3/4 | 15.0 | 7.623 | 1.7 |

64-QAM | 2/3 | 19.0 | 10.161 | 1.3 |

64-QAM | 3/4 | 21.0 | 11.439 | 1.2 |

## 3. Proposed RACA scheme

*θ*

_{3}is larger than

*θ*

_{1}. In other words, when the MS moves from position A to position C,

*θ*

_{2}is smaller than

*θ*

_{1}. Based on the changes of angle, distance, and moving speed of the MS, the potential moving path of the MS can be estimated.

*r*. Let

*d*

_{SBRS,RS}be the distance between the serving BS/RS and the RS

_{ r },

*d*

_{SBRS,MS}be the distance between the serving BS/RS and the MS, and

*d*

_{MS,RS}be the distance between the MS and the RS

_{ r }. Let

*θ*

_{ r }be the angle formed by

*d*

_{SBRS,MS}and

*d*

_{MS,RS}. According to the cosine theorem,

*θ*

_{ r }can be calculated by

*d*

_{SBRS,RS}and

*d*

_{MS,RS}at time

*t*

_{n–1}and time

*t*

_{ n }, which can be calculated by using the cosine theorem. Let Δ

*s*be the moving distance of the MS from time

*t*

_{n–1}to time

*t*

_{ n }, which can be calculated by

*t*

_{n–1}and time

*t*

_{ n }, respectively. Figure 8 shows the example of moving distance of the MS. Let ${v}_{\mathrm{MS},{t}_{n}}$ be the moving speed of the MS at time

*t*

_{ n }, which can be calculated by

*d*

_{SBRS,MS}and

*d*

_{MS,RS}at time

*t*

_{n–1}and time

*t*

_{ n }. Let ${\alpha}_{{\mathrm{RS}}_{r},{t}_{n}}$ denote the variation in angle formed by

*d*

_{SBRS,MS}and

*d*

_{MS,RS}from time

*t*

_{n–1}to time

*t*

_{ n }, which can be calculated by

_{ r }and the serving BS/RS. In contrast, when ${\alpha}_{{\mathrm{RS}}_{r},{t}_{n}}>1$, it means that the MS goes forward to the RS

_{ r }or the serving BS/RS. According to Figures 6 and 7, the possible moving direction of the MS can be observed by using the parameter ${\alpha}_{{\mathrm{RS}}_{r},{t}_{n}}.$ However, the variation in angle formed by

*d*

_{SBRS,MS}and

*d*

_{MS,RS}can only observe the possible moving direction of the MS. It is hard to know whether the MS goes forward to the RS or not. This is because that the MS may go forward to the serving BS/RS when ${\alpha}_{{\mathrm{RS}}_{r},{t}_{n}}>1$. Hence, the distance parameter must be taken into account. Let ${\beta}_{{\mathrm{RS}}_{r},{t}_{n}}$ denote the variation in distance between the MS and the RS

_{ r }from time

*t*

_{n–1}to time

*t*

_{ n }, which can be calculated by

_{ r }. In contrast, when ${\beta}_{{\mathrm{RS}}_{r},{t}_{n}}\ge 1$, it means that the MS goes away the RS

_{ r }. Let ${\omega}_{{\mathrm{RS}}_{r},{t}_{n}}$ be the measurement function of the RS

_{ r }for the MS at time

*t*

_{ n }, which can be expressed by

*t*is the time measured from

*t*

_{0}to

*t*

_{ n }after each handover and ${\epsilon}_{{t}_{n}}$ is given by the following expression:

*t*

_{n–1}to time

*t*

_{ n }, which can be calculated by

We employ ${\epsilon}_{{t}_{n}}$ as a speed parameter to adjust the measurement function ${\omega}_{{\mathrm{RS}}_{r},{t}_{n}}$. When ${\alpha}_{{\mathrm{RS}}_{r},{t}_{n}}>1\phantom{\rule{0.25em}{0ex}}\mathrm{and}\phantom{\rule{0.25em}{0ex}}{\beta}_{{\mathrm{RS}}_{r},{t}_{n}}<1$, ${\epsilon}_{{t}_{n}}$ is equal to ${\delta}_{\mathrm{MS},{t}_{n}}$. It means that the MS goes forward to the RS_{
r
} with a high opportunity. In contrast when ${\alpha}_{{\mathrm{RS}}_{r},{t}_{n}}<1\phantom{\rule{0.25em}{0ex}}\mathrm{\text{and}}\phantom{\rule{0.25em}{0ex}}{\beta}_{{\mathrm{RS}}_{r},{t}_{n}}>1$, ${\epsilon}_{{t}_{n}}$ is equal to $-{\delta}_{\mathrm{MS},{t}_{n}}$. It means that the MS goes forward to the RS_{
r
} with a low opportunity.

Due to an MS roams in the multi-hop relay networks, it must obtain the information about the neighbor BSs or RSs to prepare for switching from the current serving BS/RS to the new BS/RS. As the signal strength is poor between the serving BS/RS and the MS, the MS must seek a suitable neighbor BS or RS to perform the handover. Hence, the BS periodically calculates the SNR level and sends the information about the neighbor BSs or RSs to the MS in IEEE 802.16j systems. An MS cannot receive data packets from the serving BS/RS during the RSS measurement for the neighbor BSs and RSs. The RSS measurement overhead increases because an MS should measure the RSS of the neighbor BSs and RSs. Therefore, the network systems need more time to handle the scanning BSs and RSs when the number of BS and RS increases. It results in more overhead in the handover scanning procedure. In our proposed scheme, the measurement function is also periodically calculated by the BS and sends the information about the recommended RS to the MS for scanning. We eliminate the unnecessary associations and scanning intervals, and reduce the handover scanning procedure efficiently. The required computing time for handling the MS to switch the current serving BS/RS to the new BS/RS is also reduced. Based on the moving behavior of the MS, the proposed scheme makes an adaptive decision for dealing with the handover process.

## 4. Performance analysis

In this section, we evaluate the performance of our proposed RACA scheme using a simulation model. We describe our simulation model and illustrate the simulation results, comparing our scheme with IEEE 802.16j standard scheme. We design a simulation environment by using C#. The simulation follows the transparent relay frame structure [2] and there is no intracell interference. We assume that the relay link between the BS and the RS is in line-of-sight (LOS), while the access links between the BS and the MS and between the RS and the MS are in non-LOS. The suburban macrocellular environment is assumed. The assumptions for our simulation study are as follows:

The simulation environment is composed of 100 cells and a BS is fixed and located at the center of each cell. The coverage radius of the BS is 5 km.

The positions of the RSs are randomly distributed in the cell. For each cell, the number of RSs is equal. The coverage radius of the RS is 1 km. The numbers of RSs are 10, 30, and 50. The RSs are determined by RS deployment strategy which is out of the scope of this article.

The location of each MS is randomly distributed in each cell at the initial state. The numbers of MSs are 100, 200, 300, 400, and 500.

The speed of each MS is uniformly distributed between 0 and 120 km/h. The moving situation of each MS is random movement within the geographic area.

The average time to measure the RSS for a BS or RS is 5 ms and the average time for the handover decision phase is 110 ms [16].

The distances between MS and serving BS/RS and the RSs are estimated based on the coding rate and receiver SNR as shown in Table 2.

Performance measures obtained on the basis of ten simulation runs are plotted as a function of the average number of scanned RSs, the average number of handovers, and the average message delay. The average number of scanned RSs is defined as the average number of scanned RSs for all MSs during the simulation. Let *ns*_{m,t} denote the number of scanned RSs of the *m* th MS at time *t*. If there are *M* MSs in the system, the average number of scanned RSs can be calculated by

*t*is the simulation time from

*t*

_{ s }to

*t*

_{ f }. The average number of handovers is defined as the average number of handovers for all MSs during the simulation. The message delay is defined as the average message day time for all MSs in the handover process during the simulation. Let

*nh*

_{m,t}and

*m*

_{dm,t}, respectively, be the number of handovers and message delay time of the

*m*th MS at time

*t*. If there are

*M*MSs in the system, the average number of handovers and the message delay can be calculated by

## Conclusions

Handover process is one of the important components for QoS sensitive wireless networks. In order to accelerate the handover process and reduce the transmission interruption, efficient handover scanning procedure schemes and corresponding algorithms must be developed in an IEEE 802.16j multi-hop relay network system. In this article, a novel RACA is proposed to estimate the potential moving path of the MS by taking into account the moving behavior of the MS, and the distances among the MS, the RS, and the BS. The management information overhead can be reduced and the handover process can be accelerated. Simulation results indicate that our proposed algorithm achieves the low handover overhead and the low message delay in the IEEE 802.16j multi-hop relay network systems.

## Declarations

## Authors’ Affiliations

## References

- IEEE Std, 802.16-2009: IEEE Standard for Local and metropolitan area networks, Part 16: Air Interface for Broadband Wireless Access Systems. 2009.Google Scholar
- IEEE Standard for Local and metropolitan area networks, Part 16: Air Interface for Broadband Wireless Access Systems, Amendment for Multihop Relay Specification 2009.Google Scholar
- Ann S, Lee KG, Kim HS: A path selection method in IEEE 802.16j mobile multi-hop relay networks. In
*Proceedings of the IEEE Second International Conference on Sensor Technologies and Applications*. Cap Esterel, France; 2008:808-812.Google Scholar - Ge Y, Wen S, Ang Y-H: Analysis of optimal relay selection in 802.16 multihop relay networks. In
*Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC)*. Budapest, Hungary; 2009:1-6.Google Scholar - Ge Y, Wen S, Ang Y-H, Liang Y-C: Optimal relay selection in 802.16j multihop relay vehicular networks.
*IEEE Trans. Veh. Technol*2010, 59(5):2198-2206.View ArticleGoogle Scholar - Wang S-S, Yin H-C, Tsai Y-H, Sheu S-T: An effective path selection metric for IEEE 802.16-based multi-hop relay networks. In
*Proceedings of the IEEE Symposium on Computers and Communications (ISCC)*. Aveiro, Portugal; 2007:1051-1056.Google Scholar - Shih KP, Wang SS, Yin HC: A high spectral efficiency and load-aware metric for path selection in IEEE 802.16j multi-hop relay networks. In
*Proceedings of the IEEE Symposium on Computers and Communications (ISCC)*. Sousse, Tunisia; 2009:61-66.Google Scholar - Cho S, Kwun J, Park C, Cheon JH, Lee OS, Kim K: Hard handoff scheme exploiting uplink and downlink signals in IEEE 802.16e systems. In
*Proceedings of the IEEE 63rd Int. Conf. Vehicular Technology (VTC 2006-Spring)*. Melbourne, Australia; 2006:1236-1240.Google Scholar - Lee SH, Han Y: A novel inter-FA handover scheme for load balancing in IEEE 802.16e system. In
*Proceedings of the IEEE 63rd Int. Conf. Vehicular Technology (VTC 2007-Spring)*. Dublin, Ireland; 2007:763-767.View ArticleGoogle Scholar - Tseng PH, Feng KT: A predictive movement based handover algorithm for broadband wireless networks. In
*Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC)*. Las Vegas, Nevada, USA; 2008:2834-2839.Google Scholar - Park J, Oh S, Jeong J, Choo H: Fast handover scheme based on mobile locations for IEEE 802.16e networks. In
*Proceedings of the International Conference on Computational Science and Its Applications*. Yongin, Korea; 2009:62-67.Google Scholar - Fehri H, Chitizadeh J, Yaghmaee MH: A novel downlink handover priority scheduling algorithm for providing seamless mobility and QoS in IEEE 802.16e BWA system. In
*Proceedings of the International Conference on Communications and Mobile Computing*. 3rd edition. Kunming, Yunnan, China; 2009:227-231.Google Scholar - Ellouze R, Gueroui M, Alimi MA: Optimising handover for real-time flows in mobile wimax network. In
*Proceedings of the IEEE Symposium on Computers and Communications (ISCC)*. Sousse, Tunisia; 2009:40-45.Google Scholar - Park JH, Han KY, Cho DH: Reducing inter-cell handover events based on cell ID information in multi-hop relay systems. In
*Proceedings of the IEEE 65th Vehicular Technology Conference (VTC2007-Spring)*. Dublin, Ireland; 2007:743-747.Google Scholar - Becvar Z, Mach P, Bestak R: Optimization of handover scanning procedure in WiMAX networks with relay stations. In
*Proceedings of the 3rd International Symposium on Wireless Pervasive Computing (ISWPC 2008)*. Santorini, Greece; 2008:581-585.View ArticleGoogle Scholar - Cho S, Jang EW, Cioffi JM: Handover in multihop cellular networks.
*IEEE Commun. Mag.*2009, 47: 64-73.Google Scholar - Yun L, Ying W, Weiliang Z, Xiaohu Y: A fast handover scheme in IEEE 802.16 relay networks. In
*Proceedings of the Second International Conference on Future Networks (ICFN '10)*. Sanya, Hainan, China; 2010:243-247.Google Scholar - Sultan J, Ismail M, Misran N: Downlink performance of handover techniques for IEEE 802.16j multi-hop relay networks. In
*Proceedings of the 4th IEEE/IFIP International Conference on Internet*. Tashkent, Uzbekistan; 2008:1-4.Google Scholar - Sultan J, Misran N, Ismail M, Islam MT: Topology-aware macro diversity handover technique for IEEE 802.16j multi-hop cellular networks.
*IET Commun.*2011, 1(5):700-708.View ArticleGoogle Scholar

## Copyright

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.