Cognitive Wireless Cloud : A Network Concept to Handle Heterogeneous and Spectrum Sharing Type
Radio Access Networks
Hiroshi Harada
National Institute of Information and Communications Technolgoies
3-4 Hikarino-oka, Yokosuka, 239-0847, Japan
harada@nict.go.jp
Abstract—This paper introduces a network concept to handle heterogeneous and spectrum sharing (white space) type radio access networks, cognitive wireless cloud (CWC). This paper explains the overview, the system architecture, and the feasibility studies. As for the feasibility studies, network implementation and the development of new base station and terminal that suit for the CWC have done by using the technologies of cognitive radio and software defined radio technologies.
Keywords-component; cognitive raido, software defined radio, cognitive network, IEEE 1900.4
I.I NTRODUCTION
Currently wireless communication systems have been used for many kinds of applications and have become a gateway with next generation super broadband wired network including the Internet and users. When we prospect future wireless communication trend, the following three key words should be taken into account: (1) Broadband, (2) Localization, and (3) Ecological-coexistence (Eco-existence or E-Coexistence) as shown in Fig. 1 [1].
As for the keyword “broadband”, many standardization bodies have done standardization for broadband wireless communication systems. The transmission speed has become more than several tens Mbps for broadband wireless access (BWA) system, more than 100 Mbps for wireless local area network (WLAN), and more than 1 Gbps for wireless personal area network (WPAN), respectively and the required transmission bandwidth also has been increasing. But as the required bandwidth is wider than conventional, we confront of one problem. The issue is transmission range. If transmission power is fixed, the transmission range will be narrowed as the transmission bandwidth is wider. The future network needs to manage many number of access points that manage such broadband communication systems. So the keyword “localization” is very impotent because each access point that realizes broadband wireless communication systems needs to manage users who are in the limited area. We however also need to reduce the interference from one communication area provided by an access point to the adjacent ones. Therefore if the access point can have a function that senses its operational environment such as interference and there are some mechanisms that can share the sensing information from users between the access points, and moreover if each access point also can control its transmission power and/or frequency to be used, the communication areas provided by access points adaptively can be changed as shown in Fig. 2. A key technology to reduce the interference by using sensing is cognitive radio (CR) technology. CR is a radio or system that senses, and is aware of, its operational environment and can dynamically and autonomously adjust its radio operating parameters accordingly by collaborating wireless and wired networks [2]. As shown in Fig. 3, CR can be categorized into two: (a) Heterogeneous type and (b) Spectrum sharing (white space) type [3]. In heterogeneous type, users secure adequate bandwidth by selecting existing wireless communication systems by sensing frequency bands that systems have been allocated on and/or time slots. On the other hand, in spectrum sharing type, users sense vacant frequency bands and time slots and secure adequate bandwidth by bundling or selecting the vacant frequency bands. By using the two type CR technologies effectively, the interference is detected and
The above wireless network that co-exists several access points ecologically by using spectrum sensing function, sensing information sharing mechanism, and power and/or frequency control function is called “eco-existence (green) communication network”. NICT has researched such wireless network architecture based on CR technologies: Cognitive Wireless Cloud (CWC) [4] for more than ten years. This paper summarizes the overview, basic system architecture, and several feasibility studies regarding the CWC.
Figure 1 Three keywords.
978-1-4244-5213-4/09/ $26.00 ?2009 IEEE
Figure 2 Interference control.
II.C OGNITIVE WIREELSS CLOUD
Figure 4 shows the concept of our proposed cognitive wireless network named CWC. CWC assumes a composite wireless communication network that includes several radio access networks (RANs). Each RAN uses at least a radio access technology (RAT). Some RATs may share common frequency band. If RATs use common frequency band, the base station or access point needs to have spectrum sensing function. On the other hand user’s terminal has a function of spectrum sensing that is aware of radio operational environment surrounding the terminal. So we call the terminal cognitive terminal (CT). The terminal also has a function of reconfiguration. But we do not mind the reconfiguration scheme. To use software defined radio technology (SDR) may be one of solutions.
In Figure 4, first of all, users sense RATs or available spectrum by using cognitive radio terminal and store the results in the cognitive terminal managers (CTMs) and send the results from CTMs to the cognitive network managers (CNMs). CNMs collect the sensing information from users and status information of RANs from base station and/or access point. Based on the sensing and status information, CNMs analyze the information, and decide a recommended network policy. CNMs may be distributed to the network and they may work jointly to decide recommended RATs for the users. The recommended policy may be a list of recommended RATs that are dependent on each user’s location. When users move from one place to the other, the users newly start to sense available RATs or available spectrum and also request to CNMs to get network policies (or recommended RATs from the viewpoint of the networks). By using the sensing information, the network policies, and users’ preference, users finally decide RATs to be connected by taking user’s preference into account, because each user has some limitations to select RATs: in the case of students the most important preference may be cost to use RATs. As described in the above, CWC is user (terminal) centric network. It is therefore possible to be extended to an operator (carrier) independent networking. For optimization of radio resource management of such a scalable network having multiple operator networks and terminals, distributed optimization and management methods by using CNMs should be applied to keep using the most appropriate wireless configurations adaptively. CNM is called network reconfiguration manager (NRM) and CTM is called terminal reconfiguration manager (TRM) in IEEE 1900.4[5]
III.S YSTEM ARCHITECTURE
To realize the usage model shown in Figure 4, a fundamental system architecture shown in Figure 5 is needed. The system architecture is composed of two entities: NRMs and TRMs. NRM is an entity that manages the RANs and terminals for the optimization of spectrum usage. NRMs may be implemented in a distributed manner. TRM is an entity that manages the terminal for the optimization of spectrum usage by using user’s preferences and available context information. TRM manages sensing and sends the information to NRMs. NRMs manage to sense RAN-related context information and make policy using terminal-related and RAN-related context information. TRM receives the policy and finally decides spectrum and communication systems to be used. To do this approach, NRM connects with RAN measurement collector (RMC) and RAN reconfiguration controller (RRC). RMC is an entity that collects RAN-related context information and provides it to NRM, and may be implemented in a distributed manner and RRC is an entity that enables reconfiguration of RANs on the basis of NRM’s decision and may be implemented in a distributed manner. TRM connects with terminal measurement collector (TMC) and terminal reconfiguration controller (TRC). TMC is an entity that collects terminal-related context information and provides it to TRM. TRC is an entity that enables reconfiguration of terminal on the basis of TRM’s decision. This concept has been standardized in IEEE 1900.4 [5].
In Figure 4, there are many kinds of base station and access point. A base station or an access point senses its operational radio environment by itself and recognizes the interference level to the other base stations and access points and controls the transmission power by itself. The base station and access point are called spectrum sharing type cognitive base station (CBS). Figure 6 shows the usage model.
Fig. 3 Cognitive radio systems.
The usage model is to introduce spectrum sensing function and reconfiguration manager into base station/access point. The base station/access point is called cognitive base station (CBS). The CBS
1. Senses its radio operational environment
2. Shares the sensing information between NRM and cognitive base station reconfiguration manager (CBRM),
3. Decides spectrum and RAT(s) to be used in the CBS.
To realize the usage model shown in Figure 6, a fundamental system architecture shown in Figure 7 is needed.
The cognitive base station is composed of a modified
reconfiguration manager, measurement collector, and
reconfiguration controller: cognitive base station reconfiguration manager (CBRM), cognitive base station measurement collector (CBMC), and cognitive base station
reconfiguration controller (CBRC). CBMC shall sense its
operational environment and look for available spectrum that
will be used. Based on the spectrum sensing information,
CBRM shall decide the communication systems and communication parameters including frequency band, bandwidth, and transmission power and so on. The CBRM may communicate with other CBRMs or may communicate with NRM in the composite network. Then CBRM will request CBRM to reconfigure communication systems. Then after reconfiguration of CBS, the CBS starts to communicate with terminals by using adequate transmission power and spectrum that will not provide any interference to the other CBSs or legacy base stations.
IV. F EASIBILITY STUDY
A. Network
Figure 8 shows a prototype that realizes the system architecture in Figure 5. Figure 9 shows the status of the prototype. NRM senses the status of TRM, base stations, and access points that connected with NRM via RMC of each station or access point. If TRM requests more spectrum that cannot be handled by a base station or an access point, NRM will automatically assign other base station or access point and increase transmission speed by aggregating several RANs or RATs that operated by several base stations or access points.
B. Cognitive base station/access point
To realize the usage model shown in Figure 6, a prototype of CBS has been developed. Figures 10, 11, and Table 1 show the prototype, its configuration, and its specification,
respectively [6]. The prototype consists of three units: CPU part, FPGA part, and RF part [7]. In CPU part, CBMC,
CBRM, and CBRC were implemented as software. Two
functions are implemented in CBS, spectrum sensing and communication with users. In the spectrum sensing period,
CBS is reconfigured by spectrum sensing waveform and senses its operational frequency band and try to find available spectrum. Once the spectrum is found, CBS is reconfigured by changing waveform and communicate with users. TRM
TMC
TRC
NRM
NRM
NRM
NRM
RMC
RRC
RMC
RRC
NRM
NRM
Terminal Network TRM: Terminal Reconfiguration Manager TRC: Terminal Reconfiguration Controller TMC: Terminal Measurement Collector
NRM: Network Reconfiguration Manager RRC: RAN Reconfiguration Controller RMC: RAN Measurement Collector
Figure 5 System architecture of cognitive radio systems. Figure 4 Cognitive wireless cloud (CWC).
Figure 6 Usage model based on spectrum sharing type CBS. Figure 9 Network status monitor.
NRM
TRM
Access point status
Figure 10 Cognitive base station prototype.
Primary Operator 1Primary operator 2
Sensing
Wireless/Wired link (A kind of adhoc network)
NRM
NRM
Cognitive base s tation (CBS)
Secondary Operator 1
Cognitive terminal (CT)
Figure 7 System architecture of usage model based on spectrum sharing type CBS. Figure 11 Configuration of CBS.
Figure 8 Network prototype for CWC.
C.Terminal
To realize two usage model shown in Figures 4 and 6, a terminal that has sensing function and reconfiguration function has been developed. Figure 12 shows the prototype of cognitive radio terminal [7]. The detail information is described in [7]. The prototype utilized software defined cognitive radio (SDCR) technology and can sense selected frequency bands in 400MHz-6GHz By sensing available RANs and RATs, profiling the status of the RANs and RATs, and providing better communication systems to the users by changing waveform, the finely tuned wireless communication system can be provided. The configuration of the prototype is shown in Figure 13. The terminal is managed by TRM, TRC, and TMC and can connect with communication systems that can be aware of by the terminal and the users of the terminal have a right to access.
V.C ONCLUSION
This paper introduced a network concept to handle heterogeneous and spectrum sharing type (white space type) radio access networks, CWC. This paper explained the overview, the system architecture, and feasibility studies. As for feasibility studies, network implementation and development of new base stations and terminals that suit for the CWC have been done by using the technologies of CR and SDR technologies.
R EFERENCES
[1]H. Harada, et.al, “A cognitive Wireless Network: Cognitive Wireless
Clouds: Study of phase 1 system architecture and design of phase 2 system architecture,” Technical report of IEICE, SR 2008-37, pp.123-130, Jul. 2008.
[2]H. Harada, “Software defined radio prototype toward Cognitive Radio
Communication Systems,” IEEE Dyspan 2005, Nov. 2005.
[3]H. Harada, “Research and Development on Elemental Technologies for
Cognitive Radio Equipment,” Technical report of IEICE, April. 2006 (in Japanese).
[4]H. Harada et.al., “A Software Defined Cognitive Radio System:
Cognitive Wireless Cloud,” IEEE Globecom 2007, Washington, USA, Nov. 2007.
[5]S. Filin, et. al.,“Dynamic spectrum assignment and access scenarios,
system architecture, and procedures for IEEE P1900.4 management system,” International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008), May 2008.
[6]H. Harada et al, “Research and Development on Heterogeneous Type
and Spectrum Sharing Type Cognitive Radio Systems,” International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2009), Jun. 2009.
[7]H. Harada, “A Feasibility Study on Software Defined Cognitive Radio
Equipment,” IEEE Dyspan 2008, Oct. 2008.
Figure 13 Configuration of cognitive terminal. Figure 12 Cognitive terminal.