Elsevier

Computer Networks

Volume 56, Issue 4, 16 March 2012, Pages 1236-1248
Computer Networks

Contention based scheduling for femtocell access points in a densely deployed network environment

https://doi.org/10.1016/j.comnet.2011.12.003Get rights and content

Abstract

The proliferation of new data intensive devices has caused an enormous burden on wireless systems. A femtocell network is a promising new technology developed to meet these demands. Since each femtocell network consists of uncoordinated subnetworks that work independently, the interference between subnetworks can result in a significant degradation of the overall network capacity. In this paper, we address the interference problem between uncoordinated femtocell access points (FAPs) and propose a distributed FAP scheduling scheme in a densely deployed femtocell network where FAPs interfere with each other. In contrast to previous works that have focused on dynamic power and frequency management, our approach focuses on time sharing through FAP contention. Depending on the outcome of contention, our method selects a winning FAP to be the sole user of the next time frame. The approach operates in a fully distributed manner with help from mobile nodes (MNs). To implement this scheme, we develop a new synchronous frame structure, which uses special common control channels. Through simulations, we observe that the proposed scheme doubles the network capacity compared to the legacy non-contending scheme, and could serve as the basis for future standards on femtocell networks.

Introduction

While wireless communications originated from very humble beginnings at a few bits per second, by exchanging Morse codes, upcoming fourth generation wireless technologies (for instance, IEEE 802.11n, 802.16m and LTE-advanced) are expected to achieve wireless capacities of up to 1 Gbps. According to the Cooper’s Law, the wireless capacity has doubled every 30 months over the last 100 years [1]. The main factor of the increase in capacity has been the reduction in cell size, which contributed to an increase of 1,600 times, while advanced physical (PHY) and media access control (MAC) layer technologies, such as modulation and resource management schemes, have contributed to only an increase of 25 times in performance [1].

The important advantage of reducing the cell size is that the receiver is able to receive data packets at a high signal to noise ratio (SNR). Conventional wireless networks take advantage of this smaller cell size in increasing the wireless capacity since receivers can get the desired signal with higher strength. However, the gain obtained from the smaller cell size could get compromised by the heavy interference caused by the close proximity of neighboring cells. This means that network systems are increasingly becoming interference limited. Thus, a more important metric for network capacity is the signal to interference-plus-noise ratio (SINR) rather than SNR [2]. Therefore, each transmitter in a cell should not use its maximum power to transmit in order to reduce interference to neighboring cells. That is, simply reducing the cell size is no longer effective in increasing the network capacity in this interference limited paradigm. These days interference mitigation has become a highly challenging issue because most of the advanced wireless technologies adopt a frequency reuse factor (FRF) of one to maximize system spectral efficiency.

The latest technology in reducing the cell size is to use femtocells [3] that can be created by individual subscribers. In a femtocell network, a femtocell access point (FAP) takes charge in functioning as a macro base station (BS) to cover a small area. Since both femtocell networks and wireless local area networks (WLANs) have similar features in many things, we can easily anticipate that problems in femtocell networks will be similar with the current problems in WLANs. Due to densely deployed WLAN access points (APs), the most severe problem in WLANs is the interference between APs. This is because subscribers can install APs for themselves without consideration of other existing APs, and this problem is the same to femtocell networks. For instance, Fig. 1 shows a qualitative measurement of WLAN channel occupancy rate. We measured the channel occupation rate in a common apartment building in Korea, using a WLAN AP of Anygate RG-3000A [4]. The graph says that our AP could hear 16 APs, which implies 16 interferers co-exist in this residential area. In conclusion, to maximize the femtocell gain, femtocells should solve the interference mitigation problem as well [2], [5].

However, the interference mitigation in femtocell is harder to implement than that in conventional macrocell for several reasons [3]: First, FAPs normally use the Internet as the backbone network, so there is no explicit interface between FAPs. Second, FAPs are characterized by poorer computing power than macro BSs due to the cost down. Lastly, individual subscribers are expected to set up FAPs in an uncoordinated manner. Therefore, the interference mitigation algorithm for the femtocell network should be simple and distributed.

Combating interference is a key issue in designing a femtocell network [2], [5], [6]. There are two types of interference problems in the femtocell network: One is the interference between macrocell and femtocell, and the other between femtocells themselves. Regarding the first problem, if macrocell and femtocell networks operate in the same frequency band and try to mitigate the interference, some specification changes need to be made since femtocells are deployed in an uncoordinated manner [2]. There have been certain approaches proposed to solve this problem by controlling transmission power or by allocating different frequency bands to the macrocell and femtocells, respectively. Power control based interference mitigation schemes [7], [8], [9] tried to make the most interfered users, located between the macro BS and an FAP, have at least the same received power. In the frequency allocation based interference mitigation schemes [10], [11], the FAP operates in a different frequency band from the macro BS, resulting in higher SINR but lower spatial reuse.

For the second interference problem, power control based solutions work the same as to the first problem. They try to control FAP’s transmission power such that the strength of the desired signal at least equals that of interference signal. Many frequency based solutions have been proposed. Li et al. [12] have proposed a fractional frequency allocation scheme for FAPs through sensing each other’s interference level. However, their solutions rely on a strong assumption that each FAP fully understands the interference condition. In [13], they have proposed a distributed random access scheme that uses a hashing function to avoid interference between femtocells.

However, in a densely deployed network, the interference cannot be sufficiently mitigated by only frequency planning or power control. The research in [14] shows that deactivating some users leads to better performance than activating all the users simultaneously. To this end, a technical report [15] from 3GPP has proposed an interference reduction scheme that allocates different frame access patterns to each FAP and the macro BS, respectively, in time domain but each pattern should be allocated by a centralized controller. Another 3GPP document in [16] has considered a centralized interference mitigation approach between macrocell and femtocell. It makes the macro BS use ‘almost blank subframes’ which allow femtocells to transmit without suffering from the macrocell interference.

Rather than a centralized approach, distributed femtocell interference mitigation schemes for a densely deployed network have been recently investigated. Garcia et al. [17] has proposed a frequency allocation scheme that exploits different subchannels in a carrier aggregated frequency band. Another research [18] has formulated a coalition game for femtocell interference management. In [14], the authors have proposed a new framework to measure the interference level and a dynamic frequency allocation algorithm. However, all the investigations assumed a management entity in the backbone network to gather interference information and to make a decision in allocating time and frequency resources, or assumed interference information exchanges between FAPs through the backbone network.

Our proposed algorithm does not require any coordination between the backbone and femto networks. We aim to reduce femto-to-femto interference by time scheduling in a distributed manner. It exploits FAP contention positively, without requiring any help from the macro BS or other FAPs. It also tries to activate as many APs as possible if femtocell networks can permit. Each FAP contends with each other to get a right to use the channel. To implement our algorithm in a fully distributed manner, mobile nodes report the FAP contention result to the associated FAPs through a common control channel specified in our proposed frame structure.

This paper is organized as follows. Section 2 presents our proposed frame structure and FAP contention based scheduling algorithm. We examine the performance of our proposed scheme through analysis and simulation in Sections 3 Performance analysis, 4 Simulation results, respectively. The concluding remarks follow in Section 5.

Section snippets

Proposed channel access method

For clarity of exposition, we assume that all FAPs in the interference dominant network use only a single frequency band. In addition, we assume that the network use a time-division duplex (TDD) based orthogonal frequency division multiple access (OFDMA) system, and that frames among FAPs are synchronized. However, our proposed scheme can easily adopt other multiple access and duplex schemes such as a frequency-division duplex (FDD) based OFDMA or code division multiple access (CDMA) system.

Our

Performance analysis

In this section, we analyze the channel utilization when using our proposed FAP contention based scheduling scheme for a simple chain topology. We define the channel utilization U as the ratio of the number of active FAPs to the total number of FAPs in the network.

Simulation results

In this section, we compare the performance of our FAP contention based scheduling scheme with that of a legacy non-contention based scheme in terms of capacity and fairness for a densely deployed femtocell network. We do not compare our proposed scheme with other frequency based femto-femto interference mitigation schemes because the frequency based solutions are orthogonal with ours. Our proposed scheme reduces the femto-femto interference installed in the same frequency. Instead, we compare

Conclusion

As the market for home wireless networks grows, femtocell access points (FAPs) are expected to increase in popularity. However, for a city with a high population density, the interference from and among femtocells poses a serious challenge. In this paper, we proposed a novel frame structure for FAP contention based scheduling that aims to mitigate interference in a densely deployed wireless network. Our scheme runs in a fully distributed manner and chooses only one FAP out of interfering FAPs

Acknowledgement

This research was partially supported by the KCC (Korea Communications Commission), Korea under the R& D program supervised by the KCA (Korea Communications Agency) (KCA-2011-08913-04003).

This work was partially supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea government (MEST) (No. 2011-0027517).

Jeongkyun Yun received the B.S., M.S., and Ph.D. degrees from School of Electrical Engineering and Computer Science, Seoul National University, Seoul, Korea, in 2001, 2003, and 2008, respectively. He is currently working in LG Electronics as a senior research engineer. His research interests include future wireless LAN protocols, next generation cellular networks, and ad hoc networks.

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  • Cited by (2)

    Jeongkyun Yun received the B.S., M.S., and Ph.D. degrees from School of Electrical Engineering and Computer Science, Seoul National University, Seoul, Korea, in 2001, 2003, and 2008, respectively. He is currently working in LG Electronics as a senior research engineer. His research interests include future wireless LAN protocols, next generation cellular networks, and ad hoc networks.

    Sung-Guk Yoon is currently a Ph.D. candidate in the School of Electrical Engineering and Computer Science, Seoul National University. He received his B.S. degree from Seoul National University, in 2006. His research interests include next generation cellular networks, cross-layer optimization, resource management, and power line communications.

    Jin-Ghoo Choi received the B.S., M.S., and Ph.D. degrees in the school of Electrical Engineering & Computer Science, Seoul National University in 1998, 2000, and 2005, respectively. From 2006 to 2007, he worked for Samsung Electronics as a senior engineer. In 2009, he was with the Department of Electrical & Computer Engineering in The Ohio State University as a visiting scholar. He joined the Department of Information and Communication Engineering in Yeungnam University as a faculty member in 2010. His research interests include performance analysis of communication networks, packet scheduling policy in wireless networks, and wireless sensor network.

    Saewoong Bahk received B.S. and M.S. degrees in Electrical Engineering from Seoul National University in 1984 and 1986, respectively, and the Ph.D. degree from the University of Pennsylvania in 1991. From 1991 through 1994 he was with AT& T Bell Laboratories as a member of technical staff where he worked for AT& T network management. In 1994, he joined the school of electrical engineering at Seoul National University and currently serves as a professor. He has been serving as TPC members for various conferences including ICC, GLOBECOM, INFOCOM, PIMRC, WCNC, etc. He is on the editorial board of Journal of Communications and Networks (JCN). His areas of interests include performance analysis of communication networks and network security. He is an IEEE senior member and a member of Who’s Who Professional in Science and Engineering.

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