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New Multi-nodal Wireless Communication System Method Frank James April 14, 2014 Agenda Introduction Problem Domain Space Wireless Communication Wired Technologies/Wireless Technologies Mobile & Base Station Communication Wireless Communication Method Device & Network initiated roaming Roaming Considerations Power Spectral Density Estimation Exemplar Network Processing (Advanced) Cognitive Radio Noise “Temperature” Hardware Design (Advanced) Latest Network Processing HW Very Large Scale Integration (VLSI) DFM/DFT (1st pass Si success) 2 Problem Overview Problem Statement WiFi link layer does not support roaming efficiently across multiple access points on the network side. WiFi and Cellular base stations are not very adaptive to the RF environment. Adaptation to RF environment left to wireless devices. WiFi and Cellular technologies continue to converge. “Smart” phones support both WiFi and Cellular communication Link layer communication between the two technologies have not converged in the market space [yet] Cell sizes continue to shrink to support larger capacities Performance at the Network “Edge” continues to increase Roaming needs to be high performance between [Wi-Fi & Cellular] Access Points WiFi roaming at link layer is not well distributed or mature Reduce number of frames dropped during a roaming event How to implement Not impact existing standards (.e.g. 802.11 & UMTS) in the market place Provide ubiquitous wireless coverage across both technologies 3 Problem Overview Goal Develop an advanced multi-nodal communication system that will provide an integrated link layer for BOTH WiFi and Cellular protocols within the same cell coverage areas. Build in RF Adaptation techniques into multi-nodal wireless communication system to provide better RF service capabilities to existing infrastructure Approach Leverage existing WiFi ,Cellular and wired network protocol standards Leverage spatial diversity to extend range or seamlessly “roam” across different radio cell sizes Centralize WiFi link layer communication Utilize existing network protocol standards to utilize banck-end unreliable communication channels Integrate WiFi data path with Cellular data path subsystem Distribute WiFi link layer communication with backend system Create “Smart” WiFi & Cellular Base Stations Communicate RF parametric information to backend system so better network decisions can be made for individual devices Improve Power Spectral Density estimates so accurate information is communicated to backend system Build in RF Adaptation Control on Cell Controller 4 Communication Techniques Approach Leverage existing WiFi ,Cellular and wired network protocol standards Leverage spatial diversity to extend range or seamlessly “roam” across different radio cell sizes Centralize WiFi link layer communication 5 Communication Techniques Link Layer Mapping to Architecture 1 3 6 Communication Techniques UMTS Link Layer 3G UMTS UL: SF=Separation of data , voice, & control channels, SC=Separation of users DL: SF=Per User Separation, SC=Unique per cell Many different data and control message variants with the general format below Header Slot#0 Payload: Data, SMS/Voice, or Control Information … Slot#14 10ms 7 Communication Techniques WiFi Distributed Link Layer • • • • Flow Control (FC) is “piggy backed” with data link layer messages so fewer frames are required to support flow control Wireless Functions (FUNC) are used to perform wireless functions that measure the RF environment around each base station 802.11 & Cellular MAC are compliant link layer communication messages that performed in real time Template messages are real time messages that are transferred to base stations to be used to handle real-time message responses to wireless client devices. 8 Communication Techniques Integration of WiFi Cellular Subsystems • • The WiFi subsystem is integrated with the GGSN/PGW cellular subsystem. The GGSN/PGW cellular subsystem is responsible for providing the IP gateway services for the data services on cellular devices to the network • • In other words this services provides the IP NAT services to private IP addresses provided by the subsystem. The WiFi subsystem is also integrated with the cellular authentication services hosted through the MAP services provided through individual services provider network 9 Wireless Hardware Data Path (Cellular and WiFi) • • • Overview of the hardware state machines in a prototype hardware system architecture Hardware state machines fully autonomous termination of wireless data frames as well as real-time RF management messages. Hardware state machines provide full flow control for link layer communication path 10 Communication Techniques HW Finite State Machines Network Buffer Mgmt 1…N 802.11/Cellular Roaming HW Queue Mem CTL Input Fifo Output Fifo Mem. Cache FrameProcessor Mem. Cache FrameProcessor Mem. Cache FrameProcessor Mem. Cache FrameProcessor Mem. Cache Internal DMA System Memory Core Core Core L2 L2 Cache I-Cache L2Cache Cache I-Cache I-Cache HW Queue Frame Transmit/ Receive Parse, Classify Wireless Link Layer 802.11/Cellular Measure D-Cache L3 Cache D-Cache L3Cache Cache D-Cache L3 Coherency 1 802.11 MGMT Subsys Cellular MGMT Subsys 802.11 and Cellular Subsystems Handle Non-Real Time Link Layer Communication Execute in a Symmetric Multi-Processing Configuration 1…N Frame Buffers 1…N IV Info Key Info Eth/VLAN Template 802.11 MAC Template Cellular MAC Template Device State Frame Queue Addr Lst Cryptography Per 802.11 or Cellular User Device & FSM HW Cache Structure 2 11 Hardware Data Packet Walkthrough (Link Layer) • • • • Network frame (directed toward a wireless device is received) Either by dest. IP address or dest. MAC address. The network frame is moved to system memory for processing by downstream hardware state machines The frame is distributed [via the HW Queue] toward the Wireless MAC engine Each hardware state machine is interacts with the Coherency Fabric protocol to ensure memory caches are invalidated and updated accordingly Wireless MAC Engine 12 Hardware Data Packet Walkthrough (Link Layer) • • • • Wireless MAC Engine receives the address of an input frame from the network that is directed towards a specific frame queue ID and input/output policy (e.g. IP or MAC address of wireless device) Frame templates and a small set of CISC like instructions that are specialized for wireless frame processing. Each hardware state machine is interacts with the Coherency Fabric protocol to ensure memory caches are invalidated and updated accordingly Output sent to HW queue that then sends the offset to the portion of the frame that must be encrypted Cryptography 13 Hardware Data Packet Walkthrough (Link Layer) • • • Frame is encrypted (started at an address offset as specified by the input policy) Frame is sent to the HW Queue (only address of input & output are transmitted between hardware state machines) Each hardware state machine is interacts with the Coherency Fabric protocol to ensure memory caches are invalidated and updated accordingly 14 Communication Techniques Cryptography 5 4 RNG HW Finite State Machines Input Fifo Output Fifo HW Queue Frame Transmit/ Receive Parse, Classify Mem CTL HW Queue 2a Mem. Cache CryptoEngine Mem. Cache CryptoEngine Mem. Cache CryptoEngine Mem. Cache CryptoEngine Mem. Cache CryptoEngine Internal DMA 3 System Memory Network Buffer Mgmt 1 Frame Buffer Coherency 1…N ADDR ADDR ADDR ID ID ID Key Key Info KeyInfo Info IV Info IV Info New IV Mem. Cache Mem. Cache Prev IV Instructions Instructions Instructions 2b CryptoEngine If (New IV) == (Prev IV) { Return Error; } else { Store New IV Per IV); FlowAddr(Prev & FSM } HW Cache Structure Continue Processing… 6 15 Communication Techniques Random Number Generator (RNG) • • • • Required to support many security protocol requirements (e.g. random IV, random seeds, & random content) • IPSEC, SSL/TLS, and DTLS are examples of protocols that require random content Hardware system is required to check for generation of duplicate, consecutive random numbers per FIPS 140-2 In order to accommodate processing wireless data frames that contain random content in IV portions of the wireless frame, the cryptographic unit must generate at a rate of performance necessary to satisfy hardware frame processing. The RNG design uses asynchronous design techniques to design a RNG subsystem, one must use the instability inherent in relying upon propagation delays in a logic design that vary with temperature, voltage level fluctuation, substrate differences, and register settling time that occur through combinatorial logic designs. This technique is used to ensure a sufficient level of Entropy is achieved. 16 Communication Techniques References to be Added to Thesis Cover, T. (1972). Admissibility properties of Gilbert’s encoding for unknown source probabilities. IEEE Transactions on Information Theory, 18:216–217. Krichevsky, R. (1998). Laplace’s law of succession and universal encoding. IEEE Transactions on Information Theory, 44:296–303. McDiarmid, C. (1989). On the method of bounded differences. In Surveys in Combinatorics, pages 148–188. Cambridge University Press. Miller, G. (1955). Note on the bias of information estimates. In Information theory in psychology II-B, pages 95–100. Nemenman, I., Shafee, F., and Bialek, W. (2002). Entropy and inference, revisited. NIPS, 14. Paninski, L. (2003). Estimation of entropy and mutual information. Neural Computation, 15:1191–1253. Paninski, L. (2004). Estimating entropy on m bins given fewer than m samples. IEEE Transactions on Information Theory, 50:2200–2203. Paninski, L. (2005). Variational minimax estimation of discrete distributions under KL loss. Advances in Neural Information Processing Systems, 17. Paninski, L. (2008). A coincidence-based test for uniformity given very sparsely-sampled discrete data. IEEE Transactions on Information Theory, 54:4750–4755. Paninski, L. and Yajima, M. (2008). Undersmoothed kernel entropy estimators. IEEE Transactions on Information Theory, 54:4384–4388. 17 Communication Techniques Exemplar WiFi RF Measurement Technique • Two 802.11 radios observe the transmission of the Probe Request Messages • • • • Observed by both base stations A & B Though base station B responds to the Probe Request message, base station A is aware of the WiFi client Based upon Eb/No measured empirically from base stations A & B information is sent to the WiFi policy engine on the centralized cell controller to determine base stations A should start responding to base station management and data frames. This is referred to as soft “handover” 18 Communication Techniques WiFi Device State Machine • • • • • • Note: The WiFi state machine starts with initial power up. Most prevalent is the initiation of the association using open authentication (e.g. no authentication initiated) Association and Authentication is typically followed by an EAPOL sequence to authenticate (typically using PSK = Pre-Shared Key) Traffic Indication Map (TIM) = 2008 bits; therefore, the maximum per base station BSS is 2008 individual devices Note: When a WiFi device calculates a stronger PSD it initiates a Reassociation request to that new device If the cell controller starts transmitting data message and management message responses from a closer radio, no Reassociation process is required. 19 Communication Techniques Cellular Device State Machine • • • Just as the case with WiFi devices, the state machine starts with the power up. Paging is a cellular request initiated from a network side and is valid for 2G,3G, & 4G protocol stacks. 3G is complicated with the use of scrambling codes and per device spreading factors/codes. • • Initiated From Network However, if two radios transmit the same scrambling codes and spreading factors are used across multiple radios However, in 4G a device can use the UMTS method (from the network side) to force a handover 20 Communication Techniques Cellular Device State Machine • • • • 2G/3G devices use the following process during the cell reselection process. Note the calculation of C1 and C2 by mobile devices that are used to report measurements are used by base stations to manage handovers. In addition, neighbor lists are used to determine adjacent cell information (e.g. frequency information, ARFCN) Key Mobile Device Reselection Algorithms C1 = PSDavg - Dev_Rx_Rqdmin –max(Dev_Xmit_CCCHmax-Dev_Pwr_Class) 𝑪𝟐 = 𝑪𝟏 + 𝑪𝒆𝒍𝒍_𝑹𝒆𝒔𝒆𝒍𝒆𝒄𝒕_𝑶𝒇𝒇𝒔𝒆𝒕-max(Temp_Off_Penalty_Time) 21 RF Considerations (Roaming) Power Spectral Density Estimation Used by all devices cellular and WiFi devices to determine when to roam. Utilize a standardized PSD estimate and use the existing network stacks to perform “soft” handovers Limitations: Distance, Shadow, and Rayleigh Fading. Rayleigh fading can be addressed using orthogonal modulation techniques Distance fading can be reduced by smaller cell sizes; however, cannot be eliminated Note that the worst case distance for 802.11 is ~8400 meters (e.g. 802.11g) 𝑳𝒅 = 𝟏𝟎𝜸 𝒍𝒐𝒈 𝒅 , 𝟐 < 𝜸 < 𝟒 (dB, Urban environment) Shadow fading can be reduced by elevated antennas (e.g. dipole antennas used to reduce impedance mismatch with 50ohm connectors); however, cannot be fully eliminated. 𝑳𝒔 = 𝟏𝟎𝜸 𝒍𝒐𝒈 𝟒𝝅𝒅 𝝀 + 𝑳𝝈 , 𝑳𝝈 (dB) ~ N 𝟎, 𝝈 22 RF Considerations (Roaming) Power Spectral Density Estimation Goal: Determine the best Power Spectral Density (PSD) estimation method for the derivation of the PSD of sinusoid signals in the presence of white noise utilizing different estimation methods Approach: Conduct a statistical experiment utilizing the following different estimation methods: Blackman-Tukey Correlogram, Welch Periodogram, Yule-Walker, Burg, Covariance, Modified Covariance, and Multiple Signal Classification (MUSIC). 23 RF Considerations (Roaming) Power Spectral Density Estimation (Continued) Approach: Conduct a statistical experiment following these steps: Choose factors, levels, and ranges for the experiment Choose the response variables Choose the design of the experiment Conduct iterative experiments Perform JMP statistical analysis (using ANOVA) Based upon statistical analysis, determine conclusions and recommendations 24 RF Considerations (Roaming) Power Spectral Density Estimation (Continued) Factors: Yule-Walker, Burg, Covariance, Modified Covariance, and Multiple Signal Classification (MUSIC). Correlogram Ranges: Three different Lag levels: 10, 20, 70 point lag windows (number of input points remained constant) Periodogram Ranges: Three different shift adjustments: 10, 20, 30 point shift adjustments. Autoregressive (AR) Ranges (Yule-Walker, Burg, Covariance, Mod. Covariance, Music) : Three different model orders M: 5, 15, 30 25 RF Considerations (Roaming) (Non-Parametric Est.) Blackman-Tukey (lag window) Correlogram Results: In the experiment, increasing the lag window increased the frequency resolution; however, note that in each experiment M was much smaller than the total number of points; therefore, the frequency resolution increased. This demonstrated estimation noise, loss of resolution, and spectral leakage; however, increasing the lag window L did in fact improve spectral resolution, put it demonstrated the tradeoff between spectral resolution and estimation noise. 𝑃𝐵𝑇 𝑒 𝑗Ω = 𝑅𝐵𝑇 𝑒 𝑗Ω = 𝐿 𝑚=−𝐿 𝑤 𝑚 𝑟𝑥𝑥 𝑚 𝑒 −𝑗Ω𝑚 26 RF Considerations (Roaming) (Non-Parametric Est.) Welch Periodogram Results: In the experiment, increasing the overlap window increased the frequency resolution; however, note that I was not able to resolve the third frequency component. I kept the number of sample points constant for all tests since a longer observation does not reduce the variance. This method introduced a tapered window (e.g. Hamming window) prior to the DTFT and allowed for varying overlapping frames (e.g. shift .10, 20, 30) or maximum, approx. 2/3 overlap 𝑟𝑥𝑥 𝑛 = 𝑤 𝑛 𝑥𝑜𝑣𝑒𝑟𝑙𝑎𝑝 𝑛 P 𝑓 = 𝑇 𝑁 𝑁−1 𝑛=0 𝑟𝑥𝑥 𝑛 2 −𝑗2𝜋𝑓𝑛𝑇 𝑒 27 RF Considerations (Roaming) (Parametric Est.) Yule-Walker Results:By setting the parameter b0 = 1, the task is to estimate ak. By utilizing higher order model resolutions (e.g. higher model orders), the variance of the forward and backward linear error prediction is minimized for higher model orders; therefore, increased frequency resolution was achieved with higher model orders. The all-pole model the affect of plot smoothing. 𝑃𝐴𝑅 𝑓 = 𝑇 ∗𝑣𝑎𝑟 𝑤 𝑝 1+ 𝑘=1 𝑎𝑝 𝑘 𝑒 −𝑗2𝜋𝑘𝑓𝑇 2 Burg Results:Unlike the Yule-Walker, the Burg method does not utilize the Autocorrelation matrix. Though accuracy improved at higher model orders, the plots demonstrated spurious frequency peaks at higher model orders. 28 RF Considerations (Roaming) (Parametric Est.) Covariance/Mod. Covariance Results: Similar to the Yule-Walker method in the sense that it is also an all-pole model. This model seeks to minimize the forward error prediction with generating a non-singular event. As the model order increased, frequency resolution improved. This method demonstrated results very close to the Burg model in the sense that spurious peaks were observed at the higher model order MUSIC Results:Unlike the other Autoregressive models, the MUSIC algorithm does carry the power spectral content of signals forward. Therefore, it can only be used to identify spectral content in frequency only, not magnitude. 29 RF Considerations (Areas of Study) Space-Time adaptive interference cancellation Based upon RF spectrum sensing, share RF measurement information between base stations by Cell Controller measurement unit Canonical model coefficents communicated by Cell Controller related to RF environment (e.g. neighboring cells) Reduce adjacent channel power in adjacent cells Areas of Further Study QR decomposition Back substitution Whitening beamforming Innovative Software DSP Technology Mindspeed Coherent Logix 30 RF Considerations (Conclusions) Conclusion Based upon empirical JMP analysis results, the best performing PSD estimation methods where the high resolution: Blackman-Tukey Correlogram, Yule-Walker (AR) method, and the Modified Covariance (AR) method. JMP analysis results indicated MUSIC scores high as well for frequency estimation; however, it cannot be used for PSD estimation. Once PSD is estimated, the estimation coefficients (e.g. matrices) can be sent back to the Cell Controller by base stations. Adaptive filter can notch out interferers Combination of LPF + HPF Space-Time Adaptation techniques can be performed 31 Wireless Networks Consolidated at Central Location 32 Design/IP Verification Test (DVT) Functional/Performance Verification 33 Design Verification Model (DVM) Functional/Performance Verification 34 Verify Network Processor (Si) 35 Conclusion A new concept in regard to link layer communication as it relates to wireless devices has been introduced that provides fully integrated support for the use of 802.11 and cellular protocol stacks A new hardware implementation (e.g. start of SoC design, functional decomposition) had been introduced to support this new link layer idea that wireless data frames are processed by hardware state machines (not by software). Mobile device issues were reviewed in regard to their state machine behavior, capabilities, and typical interactions with existing wireless communication protocols. I further described how a cell controller would support these devices as well as a small research effort in regard to RF signal estimation and PSD derivation that might be implemented on mobile devices on behalf of the cell controller (e.g. network side RF measurement request). I also introduced how this might be used to change the roaming paradigm of wireless devices (strictly based upon PSD using “soft” handovers) Hardware design, development, and verification methodologies were introduced that would be employed to develop such a SoC design as well as provide functional verification after synthesis 36 Wired Technology Switch/Router Behavior 37 Wired Technology Switch/Router Behavior 38 WiFi Technology Basic Frame Types (802.11a/b/g/n) Beacon Transmissions/Probes Probe Request ESS known if no Beacon Retrieved from Beacon if Beacon messages enabled ESS identified from other Probe Requests/Responses Authentication Typically, Open Authentication Type Association ESS/BSS combination DTIM interval, Association ID utilized for power save mask Maximum wireless clients 802.1x (Typically Extensible Authentication Protocol –EAP) Authentication (4-Way Handshake) Encryption 40 WiFi Technology Basic Features IP Address Domains Can be assigned per unique ESS/BSS combination Can be assigned per unique ESS QoS Can be applied per ESS/BSS combination Can be applied per ESS combination Can be applied per IP domain Frames to RF (Weighted Fair Queue) Voice frames (Priority Queuing)/RED Security WPA (PSK,AES) (over 802.1x) Handling of Broadcast Traffic (i.e. Lowest Common Denominator for all devices associated) 41 WiFi Technology WiFi Comparison WiFi Direct Rough equivalency to entire IEEE 802.11 WiFi features P2P Group Owner (GO) acts like 802.11 Access Point WiFi Direct Features Same as WiFi QoS Security (WPA-2) Power Saving 42 WiFi Behavior NAT Performed by AP 43 WiFi Behavior NAT Performed by AP 44 Wireless Networks IP Assigned External -AP Bridge Mode 45 Wireless Networks Router External Performs NAT 46 Wireless Networks IP Address Assigned External to AP 47 Wireless Networks As Seen by Router -ARP cache 48 Wireless Networks Roaming -AP = Bridge Mode 49 Wireless Networks (Enterprise Class) 50 Wireless Networks (VPN) 51 Wireless Networks 52 Wireless Networks VPN -Mixed Environment QoS Applied Across all Access Points Based upon network configuration 53 Wireless Networks 54 Exemplar Frame Processing 55 Network Processor (Example of Latest Technology) 56 Network Processor (High Level Packet Walkthrough) 57 Network Processor (High Level Packet Walkthrough) 58 Questions??? Thank You 59 HW Finite State Machines Wireless MAC Engine Routing Frame Transmit/ Receive HW Queue Frame Classification Encryption/ Decryption Network Buffer Mgmt Pattern Matching Network Buffer Mgmt 1…N Core Core Core L2 L2 Cache L2Cache Cache I-Cache I-Cache I-Cache L3 D-Cache Cache D-Cache L3Cache Cache D-Cache L3 Coherency System Memory Mem CTL 1…N ADDR ADDR ADDR ID ID ID Key Key Info KeyInfo Info IV Info IV Info IV Info Mem. Mem. Cache Mem.Cache Cache Instructions Instructions Instructions Per Flow & FSM HW Cache Structure 60 HW Finite State Machines Wireless Link Layer 802.11/Cellular Measure Input Fifo Network Buffer Mgmt 1…N HW Queue Mem CTL I-Cache I-Cache I-Cache Mem. Cache FrameProcessor Mem. Cache FrameProcessor Mem. Cache FrameProcessor Mem. Cache FrameProcessor Mem. Cache Internal DMA System Memory Core Core Core L2 L2 Cache L2Cache Cache Queue Interface Frame Transmit/ Receive Parse, Classify Output Fifo 802.11/Cellular Roaming L3 D-Cache Cache D-Cache L3Cache Cache D-Cache L3 1…N Cryptography Frame Buffers 1…N Coherency IV Info Key Info Eth/VLAN Template 802.11 MAC Template 802.11 MGMT Subsys Cellular MGMT Subsys 802.11 and Cellular Subsystems Handle Non-Real Time Link Layer Communication Cellular MAC Template Device State Frame Queue Addr Lst Instructions Per 802.11 or Cellular User Device & FSM HW Cache Structure 61 HW Finite State Machines Wireless Link Layer 802.11/Cellular Measure Input Fifo Network Buffer Mgmt 1…N HW Queue Mem CTL I-Cache I-Cache I-Cache Mem. Cache FrameProcessor Mem. Cache FrameProcessor Mem. Cache FrameProcessor Mem. Cache FrameProcessor Mem. Cache Internal DMA System Memory Core Core Core L2 L2 Cache L2Cache Cache Queue Interface Frame Transmit/ Receive Parse, Classify Output Fifo 802.11/Cellular Roaming L3 D-Cache Cache D-Cache L3Cache Cache D-Cache L3 1…N Cryptography Frame Buffers 1…N Coherency IV Info Key Info Eth/VLAN Template 1 802.11 MGMT Subsys Cellular MGMT Subsys 802.11 and Cellular Subsystems Handle Non-Real Time Link Layer Communication 802.11 MAC Template Cellular MAC Template Device State Frame Queue Addr Lst Per 802.11 or Cellular User Device & FSM HW Cache Structure 2 62 Problem Overview Goal Develop an advanced multi-nodal communication system that will provide an integrated link layer for BOTH WiFi and Cellular protocols within the same cell coverage areas. Approach Leverage existing WiFi ,Cellular and wired network protocol standards Leverage spatial diversity to extend range or seamlessly “roam” across different radio cell sizes Centralize WiFi link layer communication Utilize existing network protocol standards to utilize banck-end unreliable communication channels Integrate WiFi data path with Cellular data path subsystem Distribute WiFi link layer communication with backend system Create “Smart” WiFi & Cellular Access Points Communicate RF parametric information to backend system so better network decisions can be made for individual devices Improve Power Spectral Density estimates so accurate information is communicated to backend system 64 Problem Overview Goal Develop an advanced multi-nodal communication system that will provide an integrated link layer for BOTH WiFi and Cellular protocols within the same cell coverage areas. Approach Leverage existing WiFi ,Cellular and wired network protocol standards Leverage spatial diversity to extend range or seamlessly “roam” across different radio cell sizes Centralize WiFi link layer communication Utilize existing network protocol standards to utilize banck-end unreliable communication channels Integrate WiFi data path with Cellular data path subsystem Distribute WiFi link layer communication with backend system Create “Smart” WiFi & Cellular Access Points Communicate RF parametric information to backend system so better network decisions can be made for individual devices Improve Power Spectral Density estimates so accurate information is communicated to backend system 65 Problem Overview Goal Develop an advanced multi-nodal communication system that will provide an integrated link layer for BOTH WiFi and Cellular protocols within the same cell coverage areas. Approach Leverage existing WiFi ,Cellular and wired network protocol standards Leverage spatial diversity to extend range or seamlessly “roam” across different radio cell sizes Centralize WiFi link layer communication Utilize existing network protocol standards to utilize banck-end unreliable communication channels Integrate WiFi data path with Cellular data path subsystem Distribute WiFi link layer communication with backend system Create “Smart” WiFi & Cellular Access Points Communicate RF parametric information to backend system so better network decisions can be made for individual devices Improve Power Spectral Density estimates so accurate information is communicated to backend system 66 Communication Techniques Problem Statements WiFi link layer does not support roaming efficiently across multiple access points on the network side. WiFi and Cellular technologies continue to converge. Performance at the Network “Edge” continues to increase “Smart” phones support both WiFi and Cellular communication Link layer communication between the two technologies have not converged in the market space [yet] Cell sizes continue to shrink to support large capacity Roaming needs to be high performance between [Wi-Fi & Cellular] Access Points WiFi roaming at link layer is not well distributed Reduce number of frames dropped during a roaming event How to implement Not impact existing standards (.e.g. 802.11 & UMTS) in the market place Provide ubiquitous wireless coverage 67 Communication Techniques Problem Statements WiFi link layer does not support roaming efficiently across multiple access points on the network side. WiFi and Cellular technologies continue to converge. Performance at the Network “Edge” continues to increase “Smart” phones support both WiFi and Cellular communication Link layer communication between the two technologies have not converged in the market space [yet] Cell sizes continue to shrink to support large capacity Roaming needs to be high performance between [Wi-Fi & Cellular] Access Points WiFi roaming at link layer is not well distributed Reduce number of frames dropped during a roaming event How to implement Not impact existing standards (.e.g. 802.11 & UMTS) in the market place Provide ubiquitous wireless coverage across both technologies 68 69 OSI Model Link Layer