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Cross layer design for Wireless networks

Cross layer design for Wireless networks. Kavé Salamatian LIP6-UPMC. Future Wireless Systems. Ubiquitous Communication Among People and Devices. Nth Generation Cellular Wireless Internet Access Wireless Video/Music Wireless Ad Hoc Networks Sensor Networks Smart Homes/Appliances

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Cross layer design for Wireless networks

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  1. Cross layer design for Wireless networks Kavé Salamatian LIP6-UPMC

  2. Future Wireless Systems Ubiquitous Communication Among People and Devices Nth Generation Cellular Wireless Internet Access Wireless Video/Music Wireless Ad Hoc Networks Sensor Networks Smart Homes/Appliances Automated Vehicle Networks All this and more…

  3. Next generation network architecture Internetworking Layer Internet Wireless PSTN Network Service Layer Mobility Services Layer Local Service Layer Access Management Layer Radio Access Layer Access Interface Layer Wireless Interface Layer Mobile Terminal Layer Mobile Application Layer

  4. IP Internet RadioL2 AccessL2 AccessL2 CoreL2 RadioL1 AccessL1 AccessL1 CoreL1 Radio Access Network Network Server(e.g. WinNT, Unix) Mobile User Equipment(e.g. Win9X, Palm OS) Radio Access Network TransportAgents Application TransportAgents RadioResourceMgmt Application IP Transport(TCP, UDP, RTP) IP Transport(TCP, UDP, RTP) Internet Protocol(IP) Internet Protocol(IP) Ethernet ATM Ethernet Modem RadioAccess • Radio-Optimized IP Networking • Transparent to TCP/IP protocols • Enables deployment of IP-based consumer applications in next generation wireless systems

  5. Separation principles • Application, transport and physical layer can be separated if : • No errors at physical layer • No losses and delays at transport layer • No fluctuations in applications rate • Each layer being perfect from the point of view of other layers Application Signal Transport Packet Physical Bits

  6. Challenges • Wireless channels are a difficult and capacity-limited broadcast communications medium • Traffic patterns, user locations, and network conditions are constantly changing • Applications are heterogeneous with hard constraints that must be met by the network • Energy and delay constraints change design principles across all layers of the protocol stack These challenges apply to all wireless networks, but are amplified in ad hoc/sensor networks

  7. d Why is Wireless Hard?The Wireless Channel • Fundamentally Low Capacity: R< B log(1+SINR) bps • Spectrum scarce and expensive • Received power diminishes with distance • Self-interference due to multipath • Channel changes as users move around • Signal blocked by objects (cars, people, etc.) • Broadcast medium – everyone interferes

  8. …AndThe Wireless Network • Link characteristics are dynamic • Network access is unpredictable and hard to coordinate • Routing often multihop over multiple wireless/wired channels • Network topology is dynamic • Different applications have different requirements Wireline Backbone

  9. Design objective • Want to provide end-to-end Properties • The challenge for this system is dynamics • Scheduling can help shape these dynamics • Adaptivity can compensate for or exploit these dynamics • Diversity provides robustness to unknown dynamics • Scheduling, adaptivity, and diversity are most powerful in the context of a crosslayer design • Energy must be allocated across all protocol layers

  10. Multilayer Design Multilayer Design • Hardware • Power or hard energy constraints • Size constraints • Link Design • Time-varying low capacity channel • Multiple Access • Resource allocation (power, rate, BW) • Interference management • Networking. • Routing, prioritization, and congestion control • Application • Real time media and QOS support • Hard delay/quality constraints

  11. Crosslayer Techniques • Adaptive techniques • Link, MAC, network, and application adaptation • Resource management and allocation (power control) • Synergies with diversity and scheduling • Diversity techniques • Link diversity (antennas, channels, etc.) • Access diversity • Route diversity • Application diversity • Content location/server diversity • Scheduling • Application scheduling/data prioritization • Resource reservation • Access scheduling

  12. Key Questions • What is the right framework for crosslayer design? • What are the key crosslayer design synergies? • How to manage its complexity? • What information should be exchanged across layers, and how should this information be used? • How do the different timescales affect adaptivity? • What are the diversity versus throughput tradeoffs? • What criterion should be used for scheduling? • How to balance the needs of all users/applications?

  13. Single user example

  14. M(g)-QAM Modulator Power: S(g) Point Selector Uncoded Data Bits One of the M(g) Points log2 M(g) Bits Adaptive Modulation and Coding in Flat Fading • Adapt transmission to channel • Parameters: power,rate,code,BER, etc. • Capacity-achieving strategy • Recent Work • Adaptive modulation for voice and data (to meet QOS) • Adaptive turbo coded modulation (<1 db from capacity) • Multiple degrees of freedom (only need exploit 1-2) • Adaptive power, rate, and compression with hard deadlines Buffer To Channel g(t) g(t) 16-QAM 4-QAM BSPK

  15. Crosslayer design in multiuser systems • Users in the system interact (interference, congestion) • Resources in the network are shared • Adaptation becomes a “chicken and egg” problem • Protocols must be distributed

  16. Wireless networks • They are formed by nodes with radios • There is no a priori notion of “links” • Nodes simply radiate energy

  17. Nodes Cooperation • Decode and forward • Why not: Amplify and Forward • Increase Signal for Receiver • Why not: Reduce Interference at Receiver

  18. How should node cooperates ? • Some obvious choices • Should nodes relay packets? • Should they amplify and forward? • Or should they decode and forward? • Should they cancel interference for other nodes? • Or should they boost each other’s signals? • Should nodes simultaneously broadcast to a group of nodes? • Should those nodes then cooperatively broadcast to others? • What power should they use for any operation? • … • Or should they use much more sophisticated unthought of strategies?

  19. Example: Six Node Network

  20. Capacity Regions (Goldsmith) (a): Single hop, no simultaneous transmissions. (b): Multihop, no simultaneous transmissions. (c): Multihop, simultaneous transmissions. (d): Adding power control (e): Successive interference cancellation, no power control. Multiple hops SIC Spatial reuse

  21. Optimal Routing • The point is achieved by the following scheduling :

  22. Adaptive Rate MAC (Kumar) • Idea: Adapt transmission rate according to channel quality • Change modulation to get higher rate if channel is good • Could send multiple packets at higher rates (A suggested cscheme) • Protocol details • RTS/CTS and Broadcast packets sent at lowest rate • Receiver measures strength of RTS • Communicates rate to sender in CTS • DATA and ACK at that rate

  23. Interaction with Min Hop Routing Protocol • Most current routing protocols are min hop • Consider DSDV for example • Chooses long hops • But long hops => low signal strength => low rates

  24. Switching off adaptation is better

  25. Routing based approach Luigi & al.

  26. Routing in wireless network • « Shortest path approche is not optimal » • Physical channel is instable • Each transmission inject interference in the network • Interference reduce capacity • Power management is needed • Make use of multi-rate and power control on WIFI card L’architecture en couches n’est pas optimale • Cross Layer approch

  27. Maximise throughput • Gupta & Kumar Rate Transmission range Node number Throughput To maximise throughput we have to maximise transmission rate and reduce interference generated by each packets

  28. Capacity Constraints

  29. Cross-Layer Approach • Routing metric • Rate • Interference • Packet Error Rate Next-Hop Data-Rate Transmission power SIR Interface characteristics

  30. Interference • Measurement: unrealistic • More neighbor => More interference • More power => More interference • Defining a interference replacement function I(P) • Minimise I(P) => Minimise Real interference

  31. Packet Error Rate (I) IPpacket IPpacket MAC MAC Convolution Coder Viterbi Decoder Deinterleaver Interleaver Modulator & Scrambler Interference Rake Receiver Noise (White or fading) Channel Single Antenna Multiple Antenna

  32. Packet Error Rate (III)

  33. Routing Strategy • Rate (Mbps) • Maximise • Interference (mW) • Minimise • PER • Minimise • Power (mW) • trade off for optimising • routing parameter • NP-Complet Problème

  34. Routingless approach Ramin & al.

  35. Ad-Hoc Network • Ad Hoc Networks function by multi-hop transport • Nodes relay packets until they reach their destinations • Must of the traffic carried by the nodes is relay traffic • The actual useful traffic per user pair is small • Intermediate nodes relay the same information • Duplicated information might be received by the receiver • More intelligent relaying is needed • Which packet to relay  • Which information to relay  • The relay nodes must only send useful information

  36. Coding for erasure channels • MDS (Maximum Distance Separable) codes • Get k packets, generates n-k redundant packets • Each combination of k packets out of n enable to retrieve the initial packets • Generating matrix • Each submatrix of is invertible • Reed Solomon codes are MDS • We suppose that sender generates m redundant packets • We suppose that relay generates l packets • How to choose m and l to achieve the bound

  37. Achievability of the capacity bound for the more capable case • Choose a code length n.Knowing packet loss matix of the netwok R and can be determined. We chose then • The code is a MDS code • The receiver is able to retrieve the k initial packets if it receives at least k packets from sender and relay together • This happen asymptotically with large n if the rate validate the bound

  38. Comments & practical consideration • Relay send only useful side information over the channel • The relay load is chosen as the minimal value which maximize the global rate • Each sender and relay can derivate the number of needed redundant packets if it know the packet loss probability matrix • The proposed scheme can be implemented very easily in WiFi based wireless network • Does not need any change to physical layer

  39. Practical implementation • 15 node distributed randomly in the environment • One Sender-Receiver pair is chosen randomly • each node have two cart WiFi, with different frequency channels f1 and f2 • If one node receive the packets • It can be a relay with probability p • The relay nodes broadcast information in the environment • There is not any routing protocol • It is done in NS

  40. Topology

  41. Throughput and relay load

  42. Toward Software radio Antenna Rx Chan LNA Dup RF/IF A/D CommonDSP platform Wideband transceiver Channel-izer NetworkI/F ATM Interface Interface Interface Upcon-verter Tx Chan D/A MCPA Cellsite controller middleware • Common technology for multiple radio platforms

  43. Conclusions • Crosslayer design needed to meet requirements and constraints of future wireless networks • Key synergies in crosslayer design must be identified • The design must be tailored to the application • Crosslayer design should include adaptivity, scheduling and diversity across protocol layers • Energy can be a precious resource that must be shared by different protocol layers • Coming Challenges • MIMO: how to take advantage of Multiple Antenna • Software Radio: How to enable adaptation of physical layer from upper layer

  44. Interesting Question • MIMO or Ad Hoc, that’s the question? • Routing can be seen as a diversity • Not shortest path !

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