Saturation Throughput Analysis of IEEE 802.11 in Presence of Non Ideal Transmission Channel and Capture Effects

In this paper, we provide a saturation throughput analysis of the IEEE 802.11 protocol at the data link layer by including the impact of both transmission channel and capture effects in Rayleigh fading environment. Impacts of both non-ideal channel and capture effects, specially in an environment of high interference, become important in terms of the actual observed throughput. As far as the 4-way handshaking mechanism is concerned, we extend the multi-dimensional Markovian state transition model characterizing the behavior at the MAC layer by including transmission states that account for packet transmission failures due to errors caused by propagation through the channel. This way, any channel model characterizing the physical transmission medium can be accommodated, including AWGN and fading channels. We also extend the Markov model in order to consider the behavior of the contention window when employing the basic 2-way handshaking mechanism. Under the usual assumptions regarding the traffic generated per node and independence of packet collisions, we solve for the stationary probabilities of the Markov chain and develop expressions for the saturation throughput as a function of the number of terminals, packet sizes, raw channel error rates, capture probability, and other key system parameters. The theoretical derivations are then compared to simulation results confirming the effectiveness of the proposed models.

💡 Research Summary

The paper presents a comprehensive saturation‑throughput analysis of IEEE 802.11 WLANs that explicitly incorporates two phenomena often omitted in classic models: non‑ideal physical‑layer channels (e.g., Rayleigh fading, AWGN) and the capture effect that can allow a packet to be successfully received even when multiple stations transmit simultaneously. The authors start by extending Bianchi’s well‑known Markov chain model of the MAC layer. For the four‑way RTS/CTS/DATA/ACK handshake they add “transmission‑failure” states that are entered whenever a packet is corrupted by the channel; the probability of such an error is denoted (p_e) and can represent any channel model, from pure AWGN to complex fading. A parallel model for the basic two‑way DCF handshake is also derived, where only ACK loss is considered.

To capture the capture phenomenon, the authors introduce a capture probability (p_{cap}). Assuming Rayleigh fading, they compute the probability that the signal‑to‑interference‑plus‑noise ratio (SINR) of the strongest transmitter exceeds a predefined threshold (\theta) when (k) stations collide. This probability is incorporated into the transition probabilities of the Markov chain, yielding a success probability
(P_{succ}=n\tau (1-\tau)^{n-1}(1-p_e)p_{cap})
where (n) is the number of contending stations and (\tau) is the per‑station transmission probability. The collision probability that does not result in capture is (P_{coll}=1-P_{idle}-P_{succ}) with (P_{idle}=(1-\tau)^n).

Solving the balance equations of the extended Markov chain provides closed‑form expressions for the stationary distribution. These are then used to derive the saturated throughput:

\