Q-Algorithm

Q-Algorithm

The epc-gen2/" class="glossary-term-link" data-term="EPC Gen2" data-definition="UHF RFID air interface standard." data-category="Standards & Protocols">EPC Gen2 adaptive anti-collision algorithm." data-category="Protocols & Communication">Q-algorithm is the adaptive anti-collision mechanism at the heart of EPC Gen2 tag singulation. It dynamically adjusts the number of time slots available for tag responses, balancing the trade-off between collision probability and empty-slot overhead. The algorithm is implemented in the reader firmware and operates transparently during every inventory round.

How It Works

The reader maintains a floating-point parameter Qfp and rounds it to the nearest integer Q. The number of slots in the current frame is 2^Q. When issuing a Query command, the reader broadcasts Q so that each tag in the population generates a random number between 0 and 2^Q - 1 as its slot counter.

After each slot, the reader observes one of three outcomes:

• Single reply: Exactly one tag responded. The reader acknowledges it, the tag flips its session flag, and both proceed.
• Collision: Multiple tags responded. The reader decrements no counters; it increases Qfp by a small constant C (typically 0.1 to 0.5) to expand the frame size.
• Empty slot: No tag responded. The reader decreases Qfp by the same constant C.

By incrementally adjusting Qfp, the algorithm converges on a frame size that matches the actual tag population, maximising throughput.

Convergence and Performance

Information-theoretic analysis shows that the optimal frame size equals the tag population size, yielding a maximum channel utilisation of approximately 36.8 percent (1/e). In practice, the Q-algorithm converges within a few dozen slots after the initial Query, even for populations exceeding 1,000 tags.

The constant C controls convergence speed. A larger C adapts faster to sudden population changes (e.g., a pallet entering a portal reader field) but oscillates more in steady state. Reader manufacturers typically set C between 0.1 and 0.3 as a default, with some models exposing it as a configurable parameter.

Interaction with Sessions and Select

The Q-algorithm operates within the scope of a single inventory round defined by the session and target flags. Tags that have already been inventoried are excluded from subsequent rounds, so the effective population shrinks as the round progresses. Combining Q-algorithm tuning with the Select command to pre-filter tag populations further improves efficiency in scenarios where only a subset of tags is of interest.

Practical Tuning

Most modern readers auto-tune Q, but system integrators should understand the starting Q value's impact. Setting an initial Q too low for a large population causes excessive collisions at the start of the round; setting it too high wastes time on empty slots. A reasonable heuristic is Q = ceil(log2(expected_tag_count)). For a pallet of 100 items, starting with Q = 7 (128 slots) is appropriate.