[21] Rudolf Ahlswede, Ning Cai, Shuo-Yen Robert Li, and Raymond W. Yeung, âNetwork information flow.,â IEEE Transactions on Information. Theory, vol. 46, no ...
Fixed / Mobile Convergence from the User Perspective for New Generation of Broadband Communication Systems Frank H.P. Fitzek† , Robert Sheahan‡ , Tatiana Kozlova Madsen† , Lester Lipsky‡ , and Ramjee Prasad† †
‡
Department of Communications Technology, Aalborg University Niels Jernes Vej 12, 9220 Aalborg Øst, Denmark, phone: +45 9635 8678, e-mail: [ff|tatiana|prasad]@kom.aau.dk Computer Science and Engineering Department, University of Connecticut 371 Fairfield Road, Storrs, CT 06269, USA phone: +1 860 486 3719, e-mail: [roberts|lester]@engr.uconn.edu
Abstract—
In this paper we introduce multiple description services for fixed/mobile convergence. The need for multiple descripted content is given in respect to the upcoming challenges in the wired as well as the wireless domain known as 4G. A novel architecture is presented that supports heterogeneous end systems without the need for transcoders. The existing problems of multiple description in terms of coding and network overhead are addressed and solutions are presented. The new novel architecture is less complex in both domains, namely the wireless and the wired one. Furthermore the architecture addresses the key research areas for the wireless world - services, spectrum, power, and complexity. I. I NTRODUCTION Future communication in fixed and mobile networks will be characterized by the heterogeneous needs of the user and limited capabilities of the end system. The latter is especially true for the wireless domain. The wireless domain was and will still be dominated by the limiting factor of the wireless bandwidth. Increasingly, consumers are demanding the same services, like streaming video and audio, on their mobile devices that they enjoy on their wired devices. Taking into consideration this demand and the previously mentioned limitations of wireless networks, we see the existing solutions for the provision of broadcast services are outdated and new solutions are needed. Take video distribution as an example broadcast service transcoding (making one or more lower resolution, and therefore lower bandwidth, copies of the original high resolution stream) was the only solution to support heterogeneous end systems in terms of dedicated data rates, frame rates, and video formats. Such a solution will cause significant additional costs for the network operator as the transcoders have to support all possible scenarios (resolutions) with each scenario requiring its own stream. The number of scenarios will increase with future communication systems as users demand services on an increasingly diverse array of devices. While this is bad enough in the wired domain with providers expected to support 56k
dialup, DSL, and T1 access, it is even worse in the wireless domain where the same content (in different resolutions) may appear on a wide variety of cell phones, PDAs, and Laptops. To be a step ahead of 3G technology, 4G must provide not only higher data rates but also some clear and evident advantage in peoples everyday lives. Therefore, the success of 4G will entail delivering rich content efficeintly despite network and terminal heterogeneity. Network heterogeneity guarantees ubiquitous connection and provision of common services (e.g., voice telephony, etc.) to the user, ensuring at least the same level of Quality of Service (QoS) when passing from one network to another. Moreover, due to the simultaneous availability of different networks, heterogeneous services are also provided to the user. Terminal heterogeneity refers to to the support of different types of terminals in terms of display size, energy consumption, portability/weight, complexity, etc. (see Figure 1). In contrast with 4G, 2G and 3G are characterized by nearly homogeneous terminals. Since 4G will encompass various types of terminals that may have to provide common services independently of their capabilities, the tailoring of the content to the end-user device will be necessary to optimize the service presentation. Furthermore, as a result of the network heterogeneity, service providers will have to carefully choose what upcoming new services they will make provisions for. These choices will be made based on the capabilities of the terminals their customers use, the requirements of the services, and the value or customer draw of the services. The decisions must be weighed carefully to prevent a sensational flop of some service. This concept is referred to as service personalization. II. M ULTI -L AYER AND M ULTIPLE D ESCRIPTION C ONTENT Multicast - reducing transmissions by allowing users with the same resolution to share the same stream - is one way to increase the bandwidth efficiency. But wireless networks have small bandwidth and greater diversity so even multicasting is not enough with video streaming. To overcome the described problems we advocate the use of multiple layered coding
coding) but provides greater flexibility. A. MDC Selection Schemes
Heterogenous terminals with their characteristics.
(MLC) and multiple descriptor coding (MDC) to support all kinds of end systems with the largest possible spectral efficiency. MLC allows splitting a given service into multiple sub streams. The core stream is referred to as the base layer and contains the most important information. Additionally enhanced layers are generated to increase the video quality. MLC combines flexibility with low overhead and is an excellent solution in the wired domain. For the wireless domain the importance of the base layer causes some problems. The wireless domain is more prone to errors so the base layer may be corrupted and the enhanced layers become useless. MDC has the capability to split the information stream into multiple sub–streams, where each of the sub–streams can be decoded without the information carried by the neighboring sub–streams and therefore has no dependencies on other sub– streams such as layered video coding has. The advantages of MDC has been exploited for multi hop networks [1], [2], Orthogonal Frequency Division Multiplexing (OFDM) [3], Multiple Input Multiple Output (MIMO) systems [4], ad–hoc networks [5], Universal Mobile Telecommunications System (UMTS) [6], Transport Control Protocol (TCP) [7] and Content Delivery Networks (CDN) [8]. Therefore MDC seems the better choice as it also generates multiple sub streams but all streams are approximately equally important and the quality depends predominantly on the number of streams received, not on which streams are received. Sub streams can be generated in a balanced (all sub streams have nearly the same bit rate) or an unbalanced way. Two different approaches to generated MDC streams are known, namely the frame splitting and the quantizer approach. In either case, the more sub streams received the higher the perceived quality. Each approach has advantages and disadvantages. Frame splitting involves less overhead to generate and receive than the quantizer approach, but some combinations may not be as smooth (a frame split MDC that produces streams A, B, C, and D will look better if the terminal receives streams A and C than if it receives A and D). Generating the MLC and MDC streams leads to an overhead compared to the single layer coding (state of the art
Sender Application
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For efficient usage of the wireless spectrum all wireless devices should be served by the same spectrum instead of allocating spectra dedicated to the different terminal classes. This feature is naturally supported when the source coding of the traffic is done as a multiple description coding. The restoration quality of the information source is proportional to the quantity of the descriptors used in the restoration process. Hence, terminals with less capabilities may simply discard or not receive some of the descriptors, while high class terminals try to receive all information. In the case of partial reception of descriptors the performance can be improved by selection strategies for the descriptors. In [9] we advocate the usage of new descriptor selection schemes for multiple description coded services. The proposed schemes differ with respect to the availability of a feedback channel and one example is given in Figure 2. All solutions are terminal oriented and are beneficial in the design of terminals that have robust and high quality services.
MCCS
DSEMDC
Application Receiver Fig. 2. Distribution of six MDC streams, where two streams are not received at the terminal due to propagation loss. The terminal has the capability to make use of a maximum number of three streams at the same time. There are four possible combination to get three out of four, but only one is optimal.
B. MDC Overhead Measurements In [9], [10], [11], [12] we have done first investigations on the overhead of multiple description for the encoding process as well as the network overhead. MDC has more overhead than MLC, but interrupting the base layer stops MLC while MDC is only stopped if all streams are stopped. Forward error correction (FEC) can reduce the chance of an error stopping the playback in MLC, but it consumes bandwidth. In the case that there is no error, the bandwidth allocated to FEC under MLC is lost, but in the case that there is no
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Fig. 3. Overhead of selected H264 video sequences in the CIF video format (288x352) for different number of sub–streams.
Fig. 4. Network overhead (RTP/UDP/IPv6) for the foreman video sequence and the quantization parameter 41.
error in MDC the extra bandwidth contributes to a higher quality image. The overhead for MDC depends on the number of MDC descriptors and the video content. In Figure 1 the overhead measurements for H.26L encoded video sequences for the CTIF video format are given. Overhead of zero refers to the same bandwidth as the single layered coding, while the overhead 1 refers to a doubling of the bandwidth. From the measurement given in Figure 3 we learn that with a very large number of descriptors (=20) the bandwidth increases by 45% in the best and 110% in the worst case. The presented measurements only represent the coding overhead, but the network overhead also has to be taken into account. For each stream the network overhead increases linearly. For IPv4 it is equal to 40J bytes where J is a number of descriptors; the transport overhead grows as 60J for IPv6. RTP/UDP/IP headers represent a large overhead, especially for MDC video streaming with high quantization values. As existing video traffic characterizations such as single and multiple layer coding differ from MDC traffic we prepared traffic traces of MDC and derived their characteristics. The traffic traces can be used by other researchers to feed their wireless network models. Furthermore additional information is presented that allows deriving the video quality after receiving a number of, possibly error–prone, sub–streams at the receiver. The results are made publicly available on our web pages [13], [14]. Other researchers are encouraged to use these traces.
compression of different sub-streams is done in a cooperative manner. Since different descriptors can be sent over different channels, MDC inherently supports multi channel communication and it is particularly suitable for combination with COHC. To efficiently maintain the context synchronization between the compressor and decompressor COHC exploits the redundancies among headers of different MDC sub-streams. It is observed that most of the fields are the same or they are highly correlated. In case a compressed packet is lost, this allows a context update using compressed headers of other MDC substreams. In this way the context synchronization is maintained without frequent full updates, guaranteing high bandwidth efficiency of the scheme. COHC compresses headers to 4 or 2 bytes (if UDP checksum is disabled) achieving compression gain of up to 95%. In Figure 4 the encoder and network overhead for the foreman video sequence using MDC is given. If no header compression is used, the total overhead increases almost linearly. Applying COHC the overhead can be kept close to the encoding overhead (low bound). For example, if three descriptors are used, the total overhead can be reduced from 150% to approximately 50%. Since the operation of COHC is totally independent from the availability of receiver feedback, this scheme supports multicast transmission of MDC video to heterogeneous terminals. It would not be possible with header compression algorithms that rely on the feedback information. In general, COHC presents an efficient solution for overhead reduction over bandwidth-limited links, both wired (e.g. low-speed serial links) and wireless (e.g. cellular systems). To support mobility of a user, last hop connection can be provided by a wireless link. COHC can serve as one of the tools helping to overcome the bandwidth limitations of e.g. cellular networks. Figure 5 illustrates possible applications of COHC in next generation cellular systems when a mobile terminal establishes parallel connections with multiple base stations or with one base station or when a relay is used for coverage extension.
C. MDC Network Overhead Reduction To make MDC attractive for bandwidth-limited links, the total overhead can be reduced by means of header compression schemes. In [15], [16], [17], [18], [19] we have introduce a novel header compression scheme for multi channel communication systems, Cooperative Header Compression (COHC). COHC exploits multiple channel diversity to achieve robustness against packet losses without the need of the feedback from the receiver. To benefit from multi path diversity, header
Fig. 5. Possible Application Fields of the Cooperative Header Compression (COHC) Meachanism.
D. MDC and multipath transmission One way 4G systems may approach the bandwidth of fixed systems is through multipath transmission. A single air link may be limited in capacity but a large number of alternate paths through a network may in aggregate provide a high capacity link. The ability to use this link requires the information flow to be divisible. Per packet routing could provide this, but it can cause problems when packets arrive out of order and does not address the problem of lost packets, so the overhead of Forward Error Correction is still required. MDC coding allows for easy division of information flow but only requires per stream routing, not per packet routing, and within a stream packets are much more likely to arrive in order. Furthermore, loss of any single stream degrades quality slightly, but does not delay or interrupt it. MDC streams can be added and removed as paths are added and removed and the overall quality remains the same as long as the number of MDC streams remains the same. The flexibility to change the number of streams and the ballance between streams makes MDC ideal for optimal link utilization in network flow problems. The classical approach to network flow problem was developed by Ford and Fulkerson in 1962 for oil pipes. Consider the following network topology given in Figure 6: One Source A is connected with Node B and Node C with capacity unit 6 and 8, respectively. The Sink F is connected with Node D and Node E with capacity unit 8 and 6, respectively. The intermediate nodes have also some capacities as given in the figure. The question is what is the optimal flow capacity and what is the related distribution? One possible solution is to use the maximum flow from path A → B → D → F with 6 capacity units and from path A → C → E → F with 3 capacity units. This would result in a total capacity of 9 capacity units. But in Figure 6 an optimal capcity with 12 capcity units is given. The solution is not obvious but can be found after some thinking. The algorithm of Ford and Fulkerson is explained in [20]. The assumption is that the flows can be split at very fine scale, or at least tradeoffs can be made between flows, a characteristic of MDC. We could apply this approach directly to the IP world using using conventional
Fig. 6.
Finding the maximum flow of the network.
coding and per packet routing, but this approach has a serious flaw. With per packet routing Node B would send half of the packets to Node D and the other half to Node E. But if Node E is disabled for a few seconds, the playback is stalled and the consumer unhappy. With MDC, playback simple gets slightly grainy for a few seconds. MDC allows using all available links at the highest capacity with minimal overhead and without catastrophic failure when nodes come in or drop out. E. MDC and Network Coding Network Coding is a mathematical transformation applied to a collection of data segments at each node in a multipath distribution network. The transformation is such that the original collection of blocks can be reconstructed from (almost) any collection of derived blocks, provided the collection of derived blocks is the same size as the original collection. No path need carry the full bandwidth of the original collection of blocks, and no node need know the network configuration (which, in fact, can change dynamically). Network Coding achieves this remarkable result by having each node form blocks that are each a linear combination (with random but recorded coefficients) of all blocks that node has received so far. The nodes exchange blocks until each node has as many derived blocks as the original collection. Each node then solves the system of simultaneous linear equations formed by the linearly combined blocks. If the space from which the random coefficients was drawn is large, the probability of one equation being a multiple of (dependent on) another is very small (and if it is, receiving one more derived block will replace the dependent equation). A system of N linearly independent equations and N unknowns has a unique solution, meaning each node can flawlessly reconstruct the original collection of blocks. This differs from simple multipath transmission of unencoded blocks in that the unencoded blocks must be routed so nodes don’t receive duplicates and nodes leaving the network may interrupt the routing of blocks. In fact, Ahlswede demonstrates [21] that there are some network topologies that cannot carry a load of unencoded parallel streams to all customers but can carry the same streams (at the same bandwidth) if Network Coding is used.
In Network Coding, the collection of blocks is often thought of as segments of a file to be shared, but they could just as easily be a slice across all MDC streams that represents one frame of multimedia content, a short segment within a single MDC stream, or a slice across a subset of the MDC streams. Each configuration would have costs and benefits and would be suited to different situations. The slice across all MDC streams removes the flexibility of MDC to drop streams - the system of equations can only be solved if there are as many equations as unknowns - but efficiently gets the MDC streams across numerous low bandwidth connections with highly dynamic behavior. This would be an excellent choice for content with an inherently limited display requirement or a large number of nodes with similar display limitations performing multihop relay to extend coverage beyond the range of the base station. In both cases, the ability to drop MDC streams is not important but the ability to divide the flow across parallel links is. Extending Network Coding in the other direction, that is, forming the blocks from several frames within a single stream, preserves the freedom to drop MDC streams and still makes excellent use of Network Coding’s ability to transport blocks through a highly dynamic network with very low overhead and only local knowledge and decisions. This approach is superior to Forward Error Correction in that it consumes far less bandwidth. The disadvantage of this approach is similar to that suffered by block based FEC schemes, it increases latency. The stream cannot be decoded until all blocks in the segment have been received. This would be an excellent choice for distributing content where a few seconds of delay is not a problem. It preserves the flexibility to use more streams to get better resolution for more powerful nodes and retains the high efficiency of Network Coding and MDC. The third configuration is a hybrid of the previous two, forming one (or more) bundles of MDC streams and using network coding to distribute slices representing a single frame within the bundle. Each node would have to receive an entire bundle to use any MDC streams out of it, but the node could receive two bundles and use all streams out of one and a fraction of the streams out of the second. If one of the bundles failed for one frame the node could simply use all of the streams out of the other bundle to get an uninterrupted transmission with a single frame of slightly lower quality. This would retain most of the flexibility of MDC and still make use of the robustness of Network Coding. Alternately, a coding scheme that allowed a system of N equations and K (≥ N) unknowns to recover N unknowns would have the flexibility of dropping frames without the overhead of receiving the fraction of a bundle that would be received but not used in the hybrid configuration. III. N OVEL F IXED /M OBILE A RCHITECTURE FOR N EW G ENERATION OF B ROADBAND C OMMUNICATION S YSTEMS Despite the bandwidth overhead we envision the following architecture for the fixed and mobile network. Without any transcoders, the MDC server generates the needed MDC streams and pumps them into the network towards Domain
Fig. 7. Novel Fixed/Mobile Architecture for New Generation of Broadband Communication Systems. Distribution of MDC streams from the server to heterogeneous terminals.
A, Domain C, and the wireless part. Domain A and Domain C could forward disjunctive descriptors towards Domain B without using the bandwidth of the backbone. In the wireless domain the descriptor will support heterogeneous terminals with high spectral efficiency (see explanation above). A. Cooperative Service Support by Customer Diversity In addition the potential of multiple description for heterogeneous terminal support, the substreams can be used to cooperate among terminals as explianed in [22], [23], [24], [25], [26]. This novel architecture idea will overcome the limitations of the cellular link capacity. As shown in Figure 1, we assume a certain number of wireless terminals in range of one base station. All terminals are served with the same multicast service. A subset of the terminals of the same multicast group is in physical proximity, such that they can communicate with each other using high-speed wireless links. Now the terminals may cooperate and receive disjunctive MDC streams and share them locally. The level of quality of service LQoS becomes then a function of the number of J cooperative terminal if enough disjunctive streams are available. LQoS = f (J)
(1)
B. Relevance for the 4G Research Some ideas have already addressed solution for the wireless 4G networks. Following the linear extension approach of existing generations will end up in many traps. One example is the energy trap. As 3G terminals are already shiping out with multiple batteries, the questions will be how many batteries will shipped out for a 4G terminal. Even more important the actual power consumption is close to a critical threshold where cooling will be needed in the terminals.
The envisioned architecture, splitting any service in autarky sub-streams, has the following capabilities regarding 4G networks • •
Support of heterogeneous terminals (see Figure 1) Cooperation among end systems – Less complex terminals – Virtual High Data Rate as the terminal only needs small data rates directly from the base station and accumulates cooperative sub-streams to form a high data stream seen from the application’s point of view. – Less spectrum is needed over the central air interface. This kind of spectrum is often purchased at auction and very expensive, while the frequencies used for short range communication are often shared and inexpensive or free. – Less power consumption – Robustness against changes on the wireless link and the number of cooperating entities. IV. C ONLCUSION
In this paper we have advocated a novel architecture for wired and wireless communication systems based on multiple description coding. Following our argumentats in the paper we believe that this approach will address the current problems of communications such as the lack of services, the need for power consumption, the usage of expensive spectrum, and the related complexity of end terminals. ACKNOWLEDGEMENT We would like to thank all our colleagues. Especially S. Frattasi for his contribution to the 4G architecture and our collegues from Arizona State University, M. Reisslein and P. Seeling for their help in hosting the traces. R EFERENCES [1] Nitin Gogate, Doo-Man Chung, Shivendra S. Panwar, and Yao Wang, “Supporting Image and Video Applications in a Multihop Radio Environment Using Path Diversity and Multiple Description Coding,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 12, no. 9, pp. 777–792, September 2002. [2] N. Gogate and S.S. Panwar, “Supporting Video/Image Applications in a Mobile Multihop Radio Environment Using Route Diversity,” in IEEE International Conference on Communications, Vancouver, Canada, June 1999, vol. 3, pp. 1701 – 1706. [3] Zhu Ji, Qian Zhang, Wenwu Zhu, Jianhua Lu, and Ya-Qin Zhang, “Video Broadcasting Over MIMO-OFDM Systems,” IEEE International Symposium on Circuits and Systems, vol. 2, no. 25-28, pp. II844 – II847, May 2003. [4] Y. Altunbas¸ak, Nejat Kamaci, and Russel M. Mersereau, “Multiple Description Coding with Multiple Transmit and Receive Antennas for Wireless Channels: The Case of Digital Modulation,” IEEE Global Telecommunications Conference, vol. 6, no. 25-29, pp. 3272–3276, November 2001. [5] Shunan Lin, Yao Wang, Shiwen Mao, and S. Panwar, “Video Transport Over Ad-Hoc Networks Using Multiple Paths,” in IEEE International Symposium on Circuits and Systems, Scottsdale, Arizona, May 2002, vol. 1 of ISCAS, pp. I57–I60. [6] M. Pereira, M. Antonini, and Michel Barlaud, “Multiple Description Video Coding for UMTS,” in Picture Coding Symposium, Saint Malo, France, April 2003.
[7] R. Puri, K. W. Lee, K. Ramchandran, and Vaduvur Bharghavan, “An Integrated Source Transcoding and Congestion Control Paradigm for Video Streaming in the Internet,” IEEE Transactions on Multimedia, vol. 3, no. 1, pp. 18–32, April 2001. [8] J. G. Apostolopoulos, W. Tan, and S. J. Wee, “Performance of a Multiple Description Streaming Media Content Delivery Network,” in IEEE Int’l Conf. on Image Processing, Rochester, New York, September 2002, vol. 2, pp. II–189 – II–192. [9] F.H.P. Fitzek, H. Yomo, P. Popovski, R. Prasad, and M. Katz, “Source Descriptor Selection Schemes for Multiple Description Coded Services in 4G Wireless Communication Systems,” in The First IEEE International Workshop on Multimedia Systems and Networking (WMSN05) in conjunction with The 24th IEEE International Performance Computing and Communications Conference (IPCCC 2005), Phoenix, Arizona, USA, Apr. 2005. [10] F.H.P. Fitzek, B. Can, R. Prasad, and M. Katz, “Overhead and Quality Measurements for Multiple Description Coding for Video Services,” in Wireless Personal Multimedia Communications WPMC 2004, Padova, Italy, Sept. 2004, pp. 524–528. [11] F.H.P. Fitzek, B. Can, R. Prasad, and M. Katz, “Traffic Analysis of Multiple Description Coding of Video Services over IP Networks,” in Wireless Personal Multimedia Communications WPMC 2004, Padova, Italy, Sept. 2004, pp. 266–270. [12] F.H.P. Fitzek, Bas¸ak Can, Ramjee Prasad, DS Park, and Youngkwon Cho, “Application of Multiple Description Coding in 4G Wireless Communication Systems,” in World Wireless Research Forum (WWRF) 8bis, Beijing, China, Feb. 2004, p. tbd. [13] Arizona State University, “Video traces for network performance evaluation,” http://trace.eas.asu.edu. [14] Aalborg University, “Video traces for network performance evaluation,” http://trace.kom.aau.dk. [15] T. K. Madsen, F.H.P. Fitzek, R. Prasad, and M. Katz, “IP Header Compression for Multicast Media Streaming in Wireless Networks,” in IEEE Vehicular Technology Conference (VTC) Fall 2005, Dallas, USA, Sept. 2005. [16] T. K. Madsen, F.H.P. Fitzek, and R. Prasad, “Performance of IP Header Compression over Correlated Multiple Channels,” in International Symposium on Wireless Personal Multimedia Communications (WPMC’05), Aalborg, Denmark, Sept. 2005. [17] T.K. Madsen and F.H.P. Fitzek, “Zero-AIC Header Compression with Multiple Description Coding for 4G Wireless Networks,” in International Workshop on Convergent Technology (IWCT) 2005, Oulu, Finland, June 2005. [18] T.K. Madsen, Y. Takatori, and F.H.P. Fitzek, “Cooperative IP Header Compression using Multiple Access Points in 4G Wireless Networks,” in 14th IST Mobile and Wireless Communications Summit, Dresden, Germany, June 2005. [19] F.H.P. Fitzek, T.K. Madsen, P. Popovski, R. Prasad, and M. Katz, “Cooperative IP Header Compression for Parallel Channels in Wireless Meshed Networks,” in IEEE International Conference on Communication (ICC), Seoul, Korea, May 2005. [20] Robert Sedgewick, Algorithms in C++, Addison Wesley, 1992. [21] Rudolf Ahlswede, Ning Cai, Shuo-Yen Robert Li, and Raymond W. Yeung, “Network information flow.,” IEEE Transactions on Information Theory, vol. 46, no. 4, pp. 1204–1216, 2000. [22] S. Frattasi and M. De Sanctis and R.L. Olsen and F.H.P. Fitzek and R. Prasad, “Innovative Services and Architectures for 4G Wireless Mobile Communication Systems,” in IEEE ISWCS, Siena, Italy, Sept. 2005. [23] S. Frattasi, A. Mihovska, F.H.P. Fitzek, S. Kyriazakos, and R. Prasad, “Service Architecture and Management in Beyond 3G Systems,” in Proceedings of the 14th Wireless World Research Forum (WWRF), San Diego (CA), USA., July 2005. [24] S. Frattasi, F.H.P. Fitzek B. Can, and R. Prasad, “Cooperative Services for 4G,” in 14th IST Mobile and Wireless Communications Summit, Dresden, Germany, June 2005. [25] S. Frattasi, H. Fathi, A. Gimmler, F.H.P. Fitzek, and R. Prasad, “A New Taxi Ride Service for the Forthcoming Generation of Intelligent Transportation Systems,” in 5th International Conference on ITS Telecommunications (ITST 2005), Brest, France, June 2005. [26] S. Frattasi, F. Fitzek, A. Mitseva, and R. Prasad, “A Vision on Services and Architectures for 4G,” in 1st CTIF B3G/4G Workshop, Aalborg, Denmark, May 2005.
