Elsevier

Neurocomputing

Volume 125, 11 February 2014, Pages 33-40
Neurocomputing

An efficient hybrid spectrum access algorithm in OFDM-based wideband cognitive radio networks

https://doi.org/10.1016/j.neucom.2012.07.041Get rights and content

Abstract

In cognitive radio networks, wideband spectrum sensing is a promising technology which allows a secondary user (SU) to detect the signals of primary users (PUs) over multiple channels, the sensing overhead is reduced effectively. Together with spectrum sensing, spectrum access strategy affects the system performance. In this paper, we propose an efficient hybrid access algorithm in OFDM-based wideband uplink model. An SU senses multiple channels via wideband spectrum sensing, and accesses these channels via a hybrid access strategy. The sensing time and transmission power of each channel are jointly optimized, in order to maximize the ergodic throughput of SUs, while the interferences to PUs are under the predefined thresholds. It is shown that the optimization problem can be formulated as a convex problem. Moreover, in order to reduce the computational complexity, two low complexity spectrum sensing and access schemes are proposed, in which the SU selects several specific channels to sense, and accesses all channels via a modified hybrid access strategy. For sensing channels selection, we present an effective selection criterion and an optimal selection order. Simulation results show that the proposed algorithm can effectively improve the system performance.

Introduction

With the increasing development of the wireless communication and services in recent years, the available spectrum becomes a limited and scarce resource. In order to increase spectrum utilization, some advance technologies in physical layer are developed, such as: MIMO–OFDM, advanced signal processing technologies [3], [4], [5]. However, traditional wireless networks are characterized by fixed spectrum-assignment policy. The recent measurements by Federal Communications Commission (FCC) show that the licensed spectrum is not fully utilized, the utilization rate always varies from 15% to 85%. This has caused significant research interest in dynamic spectrum allocation. Cognitive radio (CR) [1], [2], [6], [7], [8], which allows the spectrum sharing among licensed and unlicensed users in a dynamic spectrum access manner, becomes a promising technology. In CR, the licensed users which have been allocated spectrum are referred to as primary users (PUs), while the unlicensed users are referred to as secondary users (SUs). In practice, CR can be applied in many areas, such as smart grid and home networks [7], [8]. The application of CR is highly dependent on the SUs intelligent monitoring of the spectrum of PUs and dynamic access of the available spectrum (spectrum hole), provided that the interference is below a predefined threshold level.

Efficient and accurate spectrum sensing is one of the most important issues in CR network. The SUs perform spectrum sensing to detect the spectrum holes of PUs. The sensing time can affect the available transmission time directly, and the sensing accurate is associate with the throughput of SUs and the interference to PUs [9]. Based on the hardware capacity of SUs, spectrum sensing schemes can be classified into narrowband spectrum sensing (NSS) and wideband spectrum sensing (WSS). In the former, an SU senses one channel in a slot. In multi-channel case, the SU should sense multiple channels sequentially, which may lead to substantial overhead. Compared with NSS, exploiting a high speed A/D converter and a narrowband bandpass filter bank on the SU RF front-end, an SU can sense a set of channels simultaneously in WSS [10], [11]. The overhead is reduced efficiently, and much available spectrum can be detected. However, in prior works, the SU attempts to sense all channels, and accesses the idle channels via overlay access strategy after spectrum sensing. This will lead to heavy computational load, and reduce the ergodic throughput.

In this paper, we consider an efficient wideband hybrid access strategy algorithm in an OFDM uplink model. The sensing time and power allocation are jointly optimized in order to maximize the aggregate ergodic throughput of SU system. In the SU system, the base station (BS) performs wideband spectrum sensing to detect available spectrum opportunity. After spectrum sensing, the BS assigns the available spectrum to SUs, and SUs perform transmission to BS via hybrid access strategy. Different from overlay access strategy and underlay access strategy, under the hybrid access strategy [16], [17] (also named sensing-based spectrum sharing), an SU first listens to the spectrum band and detects the status of PUs, then adapts its transmission power based on the detected results. It also makes transmission with lower power during the busy periods under the interference threshold constraint. Thus, the SU can obtain greater ergodic throughput. In addition, we consider two low complexity spectrum sensing and access algorithms, in which the SU chooses several specific channels to sense and access. Two sensing channel selection schemes are proposed: rate aware scheme and Quality of Service (QoS) aware scheme. In the rate aware scheme, a simple and efficient sensing channels selection criterion is proposed. In the QoS aware scheme, an optimal selection order is proposed. Our analysis and simulation results show that the ergodic throughput of SU system is not affected, if we only sense a subset of the channels.

In summary, we have three major contributions in this paper.

First, we present an efficient wideband hybrid access strategy algorithm in an OFDM uplink model. The sensing time and transmission power of each channel are jointly optimized.

Second, we present a transmission rate-aware low complexity algorithm, in which the SU selects some channels for spectrum sensing, based on our proposed sensing channels selection criterion.

Finally, a QoS-aware low complexity algorithm is proposed, in which both the sensing time and transmission rate are considered. An optimal sensing channels selection order is analyzed and proposed.

The rest of this paper is organized as follows. In Section 2, we review the related work of this paper. The system model is described in Section 3. In Section 4, the sensing time and transmission power of each channel are optimized via convex optimization theory. In Section 5, we develop two low computational complexity wideband hybrid access algorithms. A simple sensing channels selection criterion and an optimal selection order are proposed and analyzed. The advantages of the proposed algorithms are illustrated by simulations in Section 6, and conclusions are drawn in Section 7.

Section snippets

Related work

Several spectrum sensing schemes have been proposed in the literature, which can be classified into two categories: narrowband spectrum sensing (NSS) [9], [12], [13] and wideband spectrum sensing (WSS) [10], [11], [14], [15]. A sensing-throughput tradeoff problem is formulated in [9] to maximize the achievable throughput of SUs under the constraint of detection probability. Cooperative sensing, which has been extensively investigated by exploiting spatial diversity to combat the unpredictable

System model

We consider an SU system which occupied a set of non-overlapping PU channels. These channels can be constituted as a wideband spectrum, and the total number is N. Let Pn(H0), (n=1,2,,N), denote the idle probability of channel n. The SU system is a centralized CR network with a base station (BS) and several SUs. The slot of SU system is divided into two slots: spectrum sensing slot and transmission slot. In the spectrum sensing slot, the BS senses the PU channels via wideband spectrum sensing.

Wideband hybrid access algorithm

In this section, we will study an optimization problem about sensing time and transmission power of each channel. The sensing time τ and power control factor λn are jointly optimized to maximize the aggregate ergodic throughput of SU system while it will not generate intolerant interference to PUs.

When an SU sends data to BS, it has two choices based on the sensing results. On the one hand, if the channel allocated to the SU is sensed as idle, the SU can access the channel with power P. Then,

Low complexity wideband hybrid access algorithm

In our proposed WHA algorithm, wideband spectrum sensing is used to detect the status of each channel. The received signal initially passes through a high speed A/D converter and then a set of individual energy detectors is used to sense the channels simultaneously. The computational complexity is large, when an SU senses all of the channels at the same time. However, for several specific channels, the SU may obtain larger ergodic throughput when it accesses these channels directly via underlay

Simulation results

In this section, we evaluate the proposed wideband hybrid access schemes. In the simulation environment, we assume that the bandwidths of each channel are the same, B=1 MHz, the frame size is T=50 ms, the decision threshold of each channel is the same, ϵn=2. The advantages of the proposed WHA algorithm, rate-aware WHA algorithm and QoS-aware WHA algorithm are illustrated in different cases. In this paper, about transmission rate, r00,n and r11,n are considered, the reason is that we calculate the

Conclusion

In this paper, we proposed the design of wideband hybrid access strategy in OFDM-based cognitive radio networks. The strategy allows that an SU senses multiple channels via wideband spectrum sensing, and accesses these channels via a hybrid access strategy. In order to limit the interference to PU under an acceptable level and maximize the aggregate ergodic throughput of SU system, the sensing time and the power control factors are jointly optimized. Furthermore, two low computational

Acknowledgment

The work in this paper is partly supported by programs of NSFC under Grant Nos. 60903170, U0835003, U1035001; Guangdong International cooperation project under Grant no. 2009B050700020; the Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP, No. 20090172120010); the Foundation for Distinguished Young Talents in Higher Education of Guangdong, China (Grant No. LYM09021); and the Opening Project of Key Lab. of Cognitive Radio and Information Processing (GUET), Ministry

Chao Yang is a Ph.D. candidate in the School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China. His research interests include cognitive radio networks, vehicular wireless network optimization, and intelligent signal processing.

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Chao Yang is a Ph.D. candidate in the School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China. His research interests include cognitive radio networks, vehicular wireless network optimization, and intelligent signal processing.

Yuli Fu is a Professor in the School of Electronic and Information Engineering, South China University of Technology. His current research interests include intelligent signal processing, wireless network optimization and compressed sensing.

Yan Zhang received the Ph.D. degree from Nanyang Technological University, Singapore. Since August 2006, he is working with Simula Research Laboratory, Lysaker, Norway, where he is currently a Senior Research Scientist. He is also an associate Professor (part-time) at the University of Oslo, Norway. He is a regional editor, associate editor on the editorial board, or guest editor of a number of international journals. He is currently serving the Book Series Editor for book series on Wireless Networks and Mobile Communications (Auerbach Publications, CRC Press, Taylor & Francis Group). His research interests include resource, mobility spectrum and data management in wireless communications and networking. Dr. Zhang serves as organizing committee chairs for many international conferences, including AINA 2011,WICON 2010. IWCMC 2010/2009, BODYNETS 2010, BROADNETS 2009, ACM MobiHoc 2008, IEEE ISM 2007, and CHINACOM 2009/2008.

Rong Yu received his B.S. degree from Beijing University of Post and Telecommunications (BUPT), Beijing, China, in 2002; and his Ph.D. from Tsinghua University, Beijing, China, in 2007. After that, he joined in the Intelligent Information Processing (IIP) Lab of South China University of Technology (SCUT). In 2010, he joined the Guangdong University of Technology, where he is an associate professor now. His research interest mainly focuses on wireless communications and networking, especially on cognitive radio, wireless sensor networks and home networking. He is the co-inventor of a number of patents and author or co-author of over 40 journals and conference papers. He serves as a member of Technical Program Committee of international conferences UIC'08, IWCMC'09, MUE'09, UC-SEC Workshop'09, ChinaCom'09, ICEE'09 and ICONI'10, etc.

Yi Liu received his Ph.D. degree in Intelligent Information Processing (IIP) Lab led by Prof. Shengli Xie at South China University of Technology (SCUT) in 2011. He is currently a working postdoctor at the School of Automation, Guangdong University of Technology. His research interests include cognitive radio networks, cooperative communications and intelligent signal processing.

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