Evolution of Heterogeneous Wireless Networks: Towards Cooperative Networks Qi Zhang
Frank H.P. Fitzek
Marcos Katz
Department of Communication, Optics & Materials Technical University of Denmark Building 343, DK-2800 Kgs. Lyngby, Denmark Email:
[email protected]
Department of Communications Technology Aalborg University Neils Jernes Vej 12, 9220 Aalborg Øst, Denmark Email:
[email protected]
VTT Technical Research Centre of Finland P.O.Box 1100 FI-90571 Oulu Finland Email:
[email protected]
Abstract— It is very challenging to implement the envisioned beyond 3G and 4G based on the conventional cellular network architecture. So a central controlled peer-to-peer network architecture is proposed, which is based on the cooperation of coexisting heterogeneous wireless networks. In the advocated architecture, the mobile terminal is capable of cellular reception of data which is then forwarded or shared among mobile devices within each others’ proximity over the short-range link. Several cooperative network demonstrators have illustrated the great potential of cooperative networks. It is en emerging trend that coexisting heterogeneous wireless networks will evolve to cooperate with each other to facilitate the centrally controlled P2P cooperative networks.
I. I NTRODUCTION In recent years one can find the terms beyond 3G and 4G in every piece of research or development plans regarding future wireless and mobile communications. What are the envisioned B3G or 4G networks? Opinions converge and diverge. For some people it is all about high data throughput capabilities, like 100 Mbps or even more, with high reliability and support of high speed mobility. Future communication networks are also expected to provide various rich content services with good quality of service (QoS). No doubt, more complex terminals are needed in B3G/4G. The-state-of-the-art, many heterogeneous wireless networks coexist with different coverage, data rates, mobility capabilities, and so on. Generally speaking, the wide access wireless networks have larger coverage and support better mobility but have lower data rates and require higher power consumption on mobile terminals, for instance cellular networks GPRS and UMTS; the local access wireless networks have higher data rates and consume much less power on the terminals but have smaller coverage with limited mobility, for instance nomadic wireless networks WLAN and Bluetooth. Although a new technology mobile WiMAX for metropolitan network has been introduced, in terms of key performance figures, WiMAX is in between wide area cellular networks and short-range networks. The tradeoff between coverage and data rate is due to the relation between radio signal attenuation and distance. As well known Shannon’s Formula has given the theoretical maximum channel capacity which depends on the bandwidth of channel
and the signal to noise ratio (SNR) of the channel. Under a given bandwidth (typically regulated spectrum), the signal to noise ratio decreases with the increasing distance between the transmitter and the receiver. Consequently the channel capacity decreases. Let us imagine if B3G/4G will be a new air-interface with all the expected features. Can this envisioned air-interface be implemented by exploiting more advanced technologies such as smart antenna or MIMO, modulation and coding scheme and others? The answer is that it is very challenging or even impossible, being the reasons of the above discussed radio signal propagation characteristics and Shannons equation. Besides that let us look at the terminal in B3G/4G. It will become more complex in order to support all these advanced technologies and a variety of services. The power demand of terminals increases much faster than the battery capacity growth speed of 10% per year. So power saving becomes another crucial issue for the success of B3G/4G. A feasible solution to implement the envisioned omnipotent wireless networks and sophisticated terminals is twofold. On the one side cellular and nomadic (short-range) heterogeneous networks should cooperate as shown in Fig. 1. On the other side the terminals forming a cluster should also collaborate. The cooperative networks may have many dimensional understandings. The envisioned cooperative networks architecture is based on cellular reception of data which is then forwarded or shared among mobile devices within each others’ proximity over the short-range link. To implement such cooperative networks, it requires that all the coexisted heterogeneous (wide access/local access) wireless networks can be designed to cooperate efficiently. And the multi-modality terminals can exploit the highly cooperative heterogeneous networks to cooperate with peers to realize the envisioned omnipotent network. Cooperation can be divided into two categories: Macro cooperation and Micro cooperation [?]. In the macro cooperation the cooperating entities are wireless terminals, virtual access points, wireless routers and other macroscopic wireless system parts [?]. The potential of macro cooperation is exploiting shorter radio propagation distance to reduce interference and
Fig. 2.
Illustration of two typical cooperative networking architectures
Section IV. In the end the conclusion is given. Fig. 1.
Evolving views of future heterogeneous wireless networks
to increase data rate. As a result, lower transmission and reception power is required. Additionally, cooperative diversity (or cooperation gain) can be exploited to form virtual antenna array (or virtual MIMO) to achieve network performance gain. Tim Shepard and Gupta & Kumar gave a theoretical capacity bound which increases with number of terminals N in the cooperative networks [?]. The essential reason is that the more wireless terminals are in the network, the more possible good paths exist to the backbone and to each other. This also fits Metcalfe’s Law1 . A good case in point of macro cooperation is hybrid ad hoc network or multihop relay cellular networks which flexibly extend the system coverage and substantially increase the link data rate with lower power output of each mobile terminal. In the micro cooperation the cooperating entities are microscopic components including processing units, functional parts and algorithms. The basic idea of micro cooperation is virtually sharing these microscopic components to obtain gain by designed cooperation mechanism. For instance, from the system’s standpoint, micro cooperation has the potential of virtually increasing cellular bandwidth, enhancing spectrum efficiency, improving reliability of wireless channel; from the terminal’s point of view, it can virtually increase battery capacity and processing capability and so on by micro cooperation. Macro and micro cooperation are just two different approaches to advance the development of wireless networks in different dimension. They can be integrated together finally. In this paper, we focus on micro cooperation and its potential in the future cooperative networks. This paper is organized as following. In Section II the cooperative wireless networking architecture and micro cooperation scenarios are addressed. Several cooperative network prototype examples and the experiment results are given in Section III. The design issue of the cooperative network are discussed in 1 Metcalfe’s Law is named after Ethernet inventor Bob Metcalfe. It is said that value of a network grows as the square of its number of users [?]
II. C OOPERATIVE W IRELESS N ETWORKING A RCHITECTURE AND S CENARIOS A. Two Cooperative Network Architectures Cooperative wireless network architectures discussed here are infrastructure based cooperative networking architectures. They can be divided into two main categories namely macro cooperation and micro cooperation. Fig. 2 shows two typical cooperative architectures. In Fig. 2(a) macro cooperative network architecture, the relay terminal can be fixed and is installed by network operator; it also can be a mobile terminal. In the latter case, packet forwarding fairness and incentive issues need to be taken into account, which will be later discussed in the Subsection IV-C. The transmission between relay terminal and mobile terminal can be implemented by different approaches; for example, by relays’ cooperative repetition, or by simultaneous transmission with space-time coding, or by selection and dynamic relay. [?] [?] [?] have produced significant amount of research on cooperative diversity. Other interesting architecture is the micro cooperative network architecture shown in Fig. 2(b). The advocated cooperative wireless networking architecture is composed of cellular mobile network and nomadic wireless network. The-state-ofart, the mobile terminal must be multi-modality terminal. In other words, the terminal is capable to communicate on both the cellular link with base station and the short-range link with peer terminals in its immediate proximity. In this cooperative architecture, the exchanged information between mobile terminals is not simple packets forwarding or relaying anymore. What, how and when to exchange the information between/among mobile terminals all depends on the targeted cooperative scenario and the designed cooperative mechanism. It is worth noticing that the so called ”cooperation” is not just ”interworking”, but it goes far beyond. They are in principle two different concepts. In heterogeneous networks, interworking means for instance that UMTS and WLAN inter-operate [?]. One way to understand the meaning of the
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Fig. 3.
Micro cooperation Scenario Matrix
”interworking” concept2 is to consider the multi modality terminal, which can not only roam between different networks seamlessly but also is capable to select one network to access when multi networks are available for it. Similarly UMTS and WiMAX interworking [?] [?], WiMAX and WLAN interworking have been proposed. No matter in which interworking case, the terminal is always working only in one network for one application at a certain duration. That is why vertical handover, seamless mobility issues are concerned when interworking means terminal roaming between heterogeneous networks. Many standardization organization like 3GPP and other researchers have worked on this in the recently years [?] [?] [?] [?]. Furthermore, so far in all proposed interworking heterogeneous networks scenario, it is always a centralized network and terminals work on a stand alone basis. The terminal has not fully used of the potential of its multimodality characteristics. However, in cooperative networks, terminals work in both the cellular and the short range nomadic networks at the same time down to packet granularity. In brief, the advocated cooperative network architecture is central controlled P2P network. B. Micro Cooperative Scenario Matrix We mainly focus on micro cooperative networks. So far we have summarized the feasible micro cooperative scenarios into an interesting matrix which is shown in Fig. 3. The interpretation of the matrix is as following. • Unicast Transport Unicast Service (UU): the mobile terminals have individual unicast services and the services are transmitted by unicast transports. Cooperative header exchange for robust header compression in VoIP is a representative example in this scenario. Here, exchanging of the compressed packet header of voice packet can help 2 There are other definition of ”interworking”. For instance, ”interworking” is also defined as that terminals from different network can communicate together with similar services.
partner to immediately recover the decoding reference when one voice packet is lost. Unicast Transport Multicast Service (UM): the mobile terminals have multicast service and this service is transported by unicast link to different terminals. Multiple Description Coding (MDC)/Multiple Layer Coding (MLC) video services or Peer-to-Peer services fit this scenario. Multicast Transport ”Unicast” Services (UM): the mobile terminals have individual different services and these services are transmitted in a multicast/broadcast fashion. For example, different DVB-H services are multicasted/broadcasted over parallel elementary streams. Multicast Transport Multicast Service (MM): the mobile terminals are interested in the same multicast service and this service is transmitted by multicast. Reliable cooperative local retransmission is a case in point.
III. C OOPERATIVE N ETWORK P ROTOTYPE E XAMPLES In this section, we introduce two implemented cooperative network prototype to illustrate the potential of cooperative networks. A. BitTorrent Application for Wireless Digital Content Download We consider a BitTorrent application for wireless content download as one representative example of the multicast service over unicast transport channels. A prototype of BitTorrent application is implemented on the Symbian OS platform using a commercially available terminal (Nokia N70) at Aalborg University. Nokia N70 is a mobile terminal with dual GPRS and Bluetooth air interfaces. We assume that a server hosts a digital content, which can be accessed by mobile terminals using the cellular air interface. If they can find partner to cooperate with each other over the short-range link, the server offers the possibility to download disjoint parts of the digital content which will be merged later over the short-range link. In order to validate the discussed principles, the first cooperative application is implemented. Two commercial terminals (Nokia N70 phones) were employed in the trial to illustrate the concept. The terminals use the Bluetooth module of the phones to communicate with each other and the GPRS to connect to base station. Using the GPRS link the terminals can reach a predefined server in the IP backbone. The IP server provides two download possibilities namely full file (stand-alone download) and split-file version, with two equally large files. In the stand-alone download, each terminal downloads the full version in a given time T, with a data rate R, spending an energy E. By the cooperative download, obviously the download time becomes nearly half, thus 'T/2. Another benefit is the reduction of the energy consumption by 44%. The reason for this behavior lies in the lower energy per bit ratio of Bluetooth than GPRS. In Fig. 4, screenshots of the application show the rates for the server (HTTP), the incoming and outgoing Bluetooth connection, and the total incoming data rate while the cooperative download is ongoing. This data rate is referred to as virtual rate, because
Fig. 4. Screenshots of the Bittorrent application for the digital content download.
it does not come directly from the base station but is usable for the application. This example shows how higher data rates (without substantially increasing complexity) and lower energy consumption (with an improved quality of service) can be achieved through cooperation. B. MDC Video Services–EDWIN Project To demonstrate the feasibility of cooperative multiple descriptions coding (MDC), the EnhanceD cooperative WIreless Networks (EDWIN) project within the C3 project of Aalborg University has been carried out. It was developed by the Center for TeleInfrastructure (CTIF) of Aalborg University. In [?] MDC was introduced for fixed/mobile convergence. In the EDWIN project the potential of cooperative wireless devices using MDC is demonstrated. Fig. 5 shows the EDWIN demonstration illustration. The demonstrator consists of one MDC video server and four clients. The MDC video server is connected with access point. The client laptops in the demonstration all have two WLAN cards: IEEE802.11b and IEEE802.11a. The clients communicate with video server through access point over IEEE 802.11b and simultaneously use IEEE802.11a for the cooperative communication among them. The main contributions of the demonstrator is the implementation of MDC in the open source project VideoLan and the IP switching device allowing the forwarding and merging of receiving of MDC streams. So the clients do not need to receive all the video descriptors. They only need to receive part of the video descriptors instead and then exchange the missed video descriptors very quickly3 over IEEE802.11a link. Furthermore, as IEEE802.11b and IEEE802.11a work on different frequencies, the two wireless systems can coexist without interference. By cooperatively receiving the video descriptor 3 Maximum data rate of IEEE802.11a is 54Mbps and that of IEEE802.11b is 11Mbps.
Fig. 5.
EDWIN project prototype illustration
over the cellular link, it virtually increases the bandwidth of cellular link. Consequently it reduces the total time of receiving all the video descriptors. Moreover power consumption of terminal is also highly reduced because average energy consumption per byte (J/MB) is much lower with IEEE802.11a than that of IEEE802.11b. For instance, the energy performance metric of Atheros AR5001X+ 802.11a WLAN card on a Pentium M laptop is 1.09J/MB but with Atheros AR5001X+ 802.11b WLAN card the metric is 5.97J/MB [?]. IV. D ESIGN C HALLENGES OF C OOPERATIVE W IRELESS N ETWORK A. Effective Self-Organizing Protocol for Short-Range Link The existed nomadic wireless networks such as WLAN and Bluetooth which are given as candidate technologies for local short-range link in [?] are inefficient to support P2P cooperation due to their intrinsic drawbacks. For instance, one master and seven slaves’ piconet structure in Bluetooth limits the size of cluster. In Bluetooth, slaves can not talk directly with each other. CSMA/CA medium access mechanism used in WLAN has bad performance (high conflict) and deteriorates cooperative gain, when the terminals increase [?]. In order to achieve more cooperative gain and widely deploy cooperative networks, efficient, generic and scalable self-organizing protocol should be designed for the short-range link. The targeted self-organizing protocol should address the following actions. • Service discovery and cluster forming: finding possible partners, spectrum scanning (predefined/ cognitive radio) • Cluster splitting and merge: scalability, interference issue, intelligent power control algorithm • Cluster membership maintenance: evaluate a new applicant, adaptive cooperative decision, timely update cluster membership • Exploiting cross platform information: exploiting multi air interface system advantage to facilitate self-organizing protocol design
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Cooperative social behavior/ relation consideration: for authentication, security
B. Cognitive Radio As we have mentioned in the Section I the upper bound channel capacity is given by Shannon’s channel capacity limit, which depends on two factors: channel spectrum bandwidth and signal noise ratio. The contradiction between propagation distance and radio signal attenuation is solved by proposed cooperative networks with the central controlled P2P architecture. As a result, the SNR performance is improved. Now to further promote system performance, what we can do is to have more spectra. But the fact is that now spectrum allocation, operating frequency and channel bandwidth has fixed regulation. Another fact is that the frequency utilization is extremely low with fixed spectrum regulation. Measurements show that less than 20% of the licensed radio spectrum is in used at any location and any given time [?]. The basic purpose of cognitive radio is to increase the frequency utilization efficiency. It has attracted many spectrum regulation organizations’ attention. Generally the challenges in cognitive radio implementation include: spectrum sensing and accurate estimating spectrum condition which requires highly sensitive radio receiver; dynamic spectrum assignment which requires efficient protocols and algorithms; adaptive transmission parameters (e.g., transmission power control, adaptive modulation, coding scheme and so on.) which result in very high computation load (on the order of billions of operation per second [?]) on the battery powered terminal. The significance of cognitive radio to cooperative networks is agile spectrum allocation for the cellular link and the shortrange link. The way of spectrum allocation and usage highly depends on the channel conditions seen by the terminals on the cellular link and the short-range link. For example, if cognitive radio is implemented in the terminals, the terminal can use ”white spectrum” 4 for the short-range communication with its peers. Furthermore, the interference introduced by the shortrange communication between peers is very low; therefore, the spectrum used in the short-range link can be reused on the short-range link by other cooperative cluster or other cellular link. The-state-of-art, multi-modality terminal is used in our cooperative network prototype. The cellular link and the shortrange link with different air interfaces have fixed, very limited individual spectrum. We can expect in the future that the available spectra for both the cellular and the short-range link will increase when terminal have cognitive capability. Consequently the achievable capacity performance of cooperative network will increase. 4 It can be the unused spectra by the cellular link as defined in the conventional cognitive radio. It can also be the spectra which suffers so severe shadowing effect, path loss and so on that cannot be used by cellular link anymore. But these spectra are good seen by terminals for short range communication.
C. Cooperation Rules from Game Theory Wireless terminals, controlled ultimately by people, are selffish and do not have incentive to cooperate by nature. The reason is that wireless terminal is always interested in maximizing its own benefit; but cooperation will costs its own resource and reduce its benefit to some extent. As a consequence, the well known ”tragedy of the commons” phenomena will emerge. Therefore in order to avoid the cooperation to collapse, robust cooperation rules and good incentives is desirable. Game theory has been widely used in biological and social science research before. In the recent years, it has started to be applied in wireless networks. For the proposed cooperative networks, game theory is an appropriate tool for terminals to take a cooperative decision (i.e., whether to cooperate or not) and have rational behavior in the cooperative networks. Now the key issue here is how to use game theory to set up cooperation rules in the cooperative networks. The ideal cooperation rules should be able not only to maximize each terminal’s individual benefit and but also to obtain maximum collective group benefit. For example, when peers exchange information or share tasks, the cooperation rules should effectively detect free rides to guarantee individual entity benefit. When peers share the common resource e.g., multiple ”white spectra”, with cooperation rules the terminals should be able to make right decision of which ”white spectrum” and which power level to use, not with greedy mode anymore. We have not designed very complicated cooperation rules in our cooperative network prototype so far. But we will integrate more rational and robust cooperation rules into cooperative networks in the near future. There are some challenges to design cooperation rules using game theory in cooperative networks. • Dynamic wireless terminal population: terminals join and leave the system independently and dynamically. • Asymmetric transaction among terminals (triangle transaction relation): for instance, terminal A needs service from terminal B and terminal B needs service from C, while C also requires service from A. How to appropriate evaluate and characterize terminals’ generosity is important. • Dynamic and heterogeneous terminal’s subjective status (e.g., battery status, CPU processing capability) and network objective status (e.g., channel condition, available spectrum, interference levels). V. C ONCLUSION We cannot expect that B3G/4G is implemented simply by an emerging new technology with conventional cellular network architecture. The clearly emerging trend is that the coexisting very heterogeneous wireless networks will evolve to cooperate with each other to facilitate the centrally controlled P2P cooperative networks. Previous research and the implemented prototypes have also shown great potential of cooperative networks. [3], [6] [4] [7], [5], [1], [2], [8]–[10] But many technical challenges of cooperative networks are still open for future research.
R EFERENCES [1] F.H.P. Fitzek, M. Katz, and Q. Zhang. Cellular Controlled Short-Range Communication for Cooperative P2P Networking. In Wireless World Research Forum (WWRF) 17, volume WG 5, Heidelberg, Germany, November 2006. WWRF. [2] Tatiana K. Madsen and Qi Zhang. Cognitive Wireless Networks: Concepts, Methodologies and Visions, chapter IP Header Compression for Cellular - Controlled P2P Networks. ISBN: 978-1-4020-5978-0. Springer, 2007. [3] T.K. Madsen, Q. Zhang, and F.H.P. Fitzek. Design and evaluation of ip header compression for cellular-controlled p2p networks. In IEEE International Conference on Communication (ICC), June 2007. [4] Q. Zhang Z. He and V.B Iversen. Trunk reservation in multi-service networks with bpp traffic. Springer Lecture Notes in Computer Science, Vol. 4396:pp. 200–212., 2007. [5] Q. Zhang, F.H.P. Fitzek, and Marcos Katz. Evolution of heterogeneous wireless networks: Towards cooperative networks. In 3nd International Conference of the Center for Information and Communication Technologies (CICT) -Mobile and wireless content, services and networks Short-term and long-term development trends, Nov 2006. [6] Q. Zhang, F.H.P. Fitzek, and Marcos Katz. Cooperative power saving strategies for ip-services supported over dvb-h networks. In Wireless communication&network conference, March 2007. [7] Qi Zhang and F.H.P. Fitzek. Designing Rules for Self-Organizing Protocols for a Cooperative Communication Architecture. an extended abstract for iwsos’06 poster section, University of Passau, Sep 2006. [8] Qi Zhang and Frank H.P. Fitzek. Cognitive Wireless Networks: Concepts, Methodologies and Visions, chapter Cooperative Retransmission for Reliable Wireless Multicast Services. ISBN: 978-1-4020-5978-0. Springer, 2007. [9] Qi Zhang, Frank H.P. Fitzek, and Villy B. Iversen. Cognitive Wireless Networks: Concepts, Methodologies and Visions, chapter Cluster based Cooperative Uplink Access in Centralized Wireless Networks. ISBN: 978-1-4020-5978-0. Springer, 2007. [10] Qi Zhang, Frank H.P. Fitzek, and Marcos Katz. Cognitive Wireless Networks: Concepts, Methodologies and Visions, chapter On the Energy Saving Potential in DVB-H Networks Exploiting Cooperation among Mobile Devices. ISBN: 978-1-4020-5978-0. Springer, 2007.
