Communication Theory as Applied to Wireless Sensor Networks muse.

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Presentation transcript:

Communication Theory as Applied to Wireless Sensor Networks muse

Outline Sensor network contraints Digital modulation Source coding and Channel coding MAC Synchronization Synthesis: Energy and bandwidth requirements

Source Coding Motivation Lossless Lossy Source Coding

Lossless Compression Zip files Entropy coding (e.g., Huffman code) Source Coding

Lossless Compression Approaches for Sensor Networks Constraints Run length coding Sending only changes in data Source Coding

Lossy Compression Rate distortion theory (general principles) JPEG Source Coding

Example of Lossy Compression - JPEG

Another comparison

Lossy Compression Approaches for Sensor Networks Constraints Transformations / Mathematical Operations Predictive coding / Modeling Source Coding

Example Actions by Nodes Adaptive Sampling Censoring Source Coding

In-Network Processing Data Aggregation Source Coding

Outline Sensor network contraints Digital modulation Source coding and Channel coding MAC Synchronization Synthesis: Energy and bandwidth requirements

Channel Coding (FEC) Motivation Block codes Convolution codes Channel Coding

Channel Coding Approaches for Sensor Networks Coding constraints Block coding Channel Coding

Example: Systematic Block Code Channel Coding

Alternative: Error Detection Motivation CRC Channel Coding

Performance Benefits Costs Channel Coding Fig. Lathi

Outline Sensor network contraints Digital modulation Source coding and Channel coding MAC Synchronization Synthesis: Energy and bandwidth requirements

Sharing Spectrum MAC Fig. Frolik (2007)

MAC Motivation Contention-based Contention-free MAC

ALOHA (ultimate in contention) Method Advantages Disadvantages MAC

CSMA (contentious but polite) Method Advantages Disadvantages MAC

Throughput comparison MAC

Contention Free Approaches RTS/CTS Reservations MAC

MAC for Sensor Networks: Beacon enabled mode for star networks MAC

Bandwidth details: GHz band ( GHz) Sixteen channels spaced at 5 MHz (CH 11 – 26) Data rate – 250 kbps Direct sequence spread spectrum (DSSS) 4 bits → symbol → 32 chip sequence Chip rate of 2 Mcps Modulation – O-QPSK Total bandwidth requirement: ~3 MHz MAC

DSSS Motivation Operation MAC

Outline Sensor network contraints Digital modulation Source coding and Channel coding MAC Synchronization Synthesis: Energy and bandwidth requirements

Synchronization Motivation Categories Synchronization

Node Scheduling Sleep Listening Transmitting Synchronization

Sleep Scheduling for Sensor Networks: S-MAC Synchronization

Synchronizing for Effective Communications Carrier Bit/Symbol Frame Synchronization

Outline Sensor network contraints Digital modulation Source coding and Channel coding MAC Synchronization Synthesis: Energy and bandwidth requirements

Putting the Pieces Together

Synthesis: Energy and Bandwidth M-ary Signaling Channel Coding Energy & Bandwidth

Sensor Network Example 1: Single vs. Multihop Multihop Single hop Energy & Bandwidth

Sensor Network Example 2: Polling vs. Pushing Polling Pushing Energy & Bandwidth

Conclusions A digital communications approach to WSN has advantages in robustness, energy, and bandwidth performance Source coding reduces overall system level energy requirements Simple channel coding schemes improve data reliability minimizing the need for retransmissions muse

Conclusions - 2 MAC and routing strategies should be chosen with an eye towards network architecture – cross-layer design Node synchronization must occur regularly due to clock drift between nodes Simple digital communication techniques enable low-energy, low-bandwidth WSN system requirements muse

What to know more? B. Lathi, Modern Analog and Digital Communication Systems, 3 rd ed., Oxford, B. Krishnamachari, Networking Wireless Sensors, Cambridge Press, J. Frolik, “Implementation Handheld, RF Test Equipment in the Classroom and the Field,” IEEE Trans. Education, Vol. 50, No. 3, August 2007.