# Analytical Comparison Between IEEE 802.11p and IEEE 802.11bd Based on an Extended Bianchi Model

Paul Muhlethaler

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# Analytical Comparison Between IEEE 802.11p and IEEE 802.11bd Based on an Extended Bianchi Model

Paul Muhlethaler

AIO - Inria Paris

Email: Paul.Muhlethaler@inria.fr

**Index Terms**—IEEE 802.11p, IEEE 802.11bd, vehicular networks, V2X communications, analytical modeling, Bianchi model, saturation throughput, MAC layer delay

**Abstract**—IEEE 802.11p has long been the baseline for vehicular communication (V2X) applications, while IEEE 802.11bd has emerged as its successor, promising higher reliability, throughput, and backward compatibility. In this paper, we compare the performance of both standards using an analytical model inspired by Bianchi's saturation throughput analysis. We propose a modification to the original Bianchi model to account for physical layer enhancements in IEEE 802.11bd by introducing a success probability even in the presence of collisions. Specifically, we incorporate a tunable parameter to model the impact of advanced features such as MIMO, higher-order modulation, and cooperative retransmission, which improve the likelihood of packet delivery despite contention. The modified model enables a more accurate analytical comparison between the two standards under saturated traffic conditions. Our analysis reveals the extent to which IEEE 802.11bd mitigates the negative impact of collisions and enhances throughput performance compared to its predecessor.

## I. INTRODUCTION

Vehicular communication systems are increasingly critical for enabling road safety, traffic efficiency, and autonomous driving. These systems must operate under strict latency and reliability constraints, especially for safety-critical applications. IEEE 802.11p, standardized in 2010, was designed to support such requirements by enabling wireless access in vehicular environments (WAVE). It operates in the 5.9 GHz band using a modified version of IEEE 802.11a, adapted to 10 MHz channels to improve robustness under high mobility conditions. Despite its adoption in early V2X deployments, IEEE 802.11p has inherent limitations in terms of achievable throughput, support for advanced modulation schemes, and resilience under high-density scenarios.

## II. RELATED WORKS

The evolution of V2X communication standards has been widely studied in the literature, reflecting both academic and industrial interest in enabling reliable, low-latency, and scalable communication between vehicles and infrastructure. This section provides an overview of foundational works, analytical models, and recent comparative studies that have

shaped the understanding and development of IEEE 802.11p and its successor, IEEE 802.11bd.

### A. Foundational Studies on DSRC and IEEE 802.11p

One of the earliest and most cited works is by Kenney [1], who presents a detailed overview of the Dedicated Short Range Communications (DSRC) system in the United States. The paper discusses the regulatory background, system architecture, and the role of IEEE 802.11p in supporting low-latency V2X communication. Kenney's study emphasizes the simplicity and effectiveness of 802.11p for basic safety applications, while also noting its inherent limitations in terms of scalability and spectrum efficiency.

Subsequent studies have evaluated the performance of 802.11p in diverse scenarios. For example, Mecklenbräuker et al. [2] assess the robustness of 802.11p in urban and highway environments, and identify performance degradation due to multipath fading and Doppler effects in high-mobility conditions.

### B. Analytical Models and MAC Layer Performance

A foundational contribution to understanding IEEE 802.11 MAC behavior comes from Bianchi [3], who proposed a Markov chain model to analyze the Distributed Coordination Function (DCF) under saturated traffic conditions. Although developed for general IEEE 802.11 networks, Bianchi's model has been extensively used to analyze 802.11p's performance. The model allows the derivation of throughput, collision probability, and delay as functions of the transmission probability $\tau$ and the number of contending nodes.

Building on this model, researchers such as Fàbrega and Reñé [4] extended the analysis to vehicular-specific parameters, incorporating variable backoff schemes and prioritization mechanisms based on the Enhanced Distributed Channel Access (EDCA) of 802.11e.

### C. Limitations of IEEE 802.11p and motivation for IEEE 802.11bd

Numerous studies have identified critical limitations of IEEE 802.11p that hinder its effectiveness in high-density and high-data-rate scenarios. These include excessive collision
rates under load, inefficient spectrum use due to CSMA/CA, and the absence of advanced PHY-layer features such as MIMO or OFDMA. These issues have motivated the IEEE 802.11 working group to initiate the Next-Generation V2X (NGV) project, resulting in IEEE 802.11bd.

Karagiannis et al. [5] provide a comprehensive technical overview of the IEEE 802.11bd standard. Their work details enhancements such as dual subcarrier transmission, MIMO support, 256-QAM modulation, and backward compatibility mechanisms. They also highlight the standardization challenges, coexistence requirements, and testing methodologies under consideration by the IEEE.

### D. Performance Comparisons and Real-World Evaluations

Several system-level simulation studies and experimental evaluations have been conducted to compare the performance of 802.11bd with 802.11p and alternative technologies such as 3GPP C-V2X. Jacob et al. [6] simulate both standards in highway scenarios and demonstrate that 802.11bd significantly improves packet delivery ratio and throughput under high vehicular density.

Likewise, Mahmood et al. [7] explore the coexistence and complementarity of IEEE 802.11bd and C-V2X, recommending hybrid architectures where both technologies can be leveraged for different V2X use cases. These studies contribute to the ongoing discussion about whether 802.11bd and C-V2X should be seen as competing or complementary technologies.

### E. Industrial and Collaborative Research Projects

In addition to academic work, several industry-driven initiatives such as the CAR 2 CAR Communication Consortium (C2C-CC) and the CAMP V2X project in the United States have published technical white papers and deployment guidelines. These documents provide insights into interoperability requirements, spectrum policy challenges, and migration strategies from DSRC to next-generation standards.

In Europe, large-scale projects like C-ROADS and 5GCAR have explored the integration of vehicular communication standards into real-world infrastructure and policy frameworks, often evaluating both IEEE and 3GPP-based solutions.

### F. Summary

In response to these limitations, IEEE 802.11bd has been developed as the next-generation standard for vehicular communications. It aims to enhance the capabilities of IEEE 802.11p by introducing features such as MIMO (Multiple Input Multiple Output), higher-order modulation (e.g., 64-QAM, 256-QAM), LDPC coding, and improved medium access control. Moreover, IEEE 802.11bd maintains backward compatibility with IEEE 802.11p, making it suitable for incremental deployment.

## III. BIANCHI'S MODEL AND ITS ADAPTATION TO IEEE 802.11BD

Bianchi's model [3] describes the behavior of the CSMA/CA protocol under saturation using a two-dimensional

<figure><img src="image_2.png" /><figcaption>Fig. 1. Simplified two-stage Markov Chain for the IEEE 802.11 DCF backoff process</figcaption></figure>

Markov chain. Each node is always backlogged and attempts transmission with a probability $\tau$. The collision probability $p$ and transmission probability $\tau$ are coupled:

$$ \tau = \frac{2(1 - 2p)}{(1 - 2p)(W_0 + 1) + pW_0(1 - (2p)^m)} \quad (1) $$

$$ p = 1 - (1 - \tau)^{n-1} \quad (2) $$

IEEE 802.11bd introduces diversity and redundancy techniques at the physical and MAC layers, such as MIMO and retransmissions over multiple channels. These features increase the probability of successful reception, even after collision events that would cause failure in IEEE 802.11p.

To model this, we redefine the effective failure probability as:

$$ p' = p \cdot (1 - \theta) \quad (3) $$

where quantifies the likelihood of success after a collision due to the enhanced features in 802.11bd.

Replacing with in Bianchi's model yields the modified equation for:

$$ \tau = \frac{2(1 - 2p')}{(1 - 2p')(W_0 + 1) + p'W_0(1 - (2p')^m)} \quad (4) $$

The collision probability is thus:

$$ p' = (1 - \theta) * (1 - (1 - \tau)^{n-1}) \quad (5) $$

### A. Throughput Expression Based on Bianchi's Model

In Bianchi's model for IEEE 802.11 DCF, assuming a saturated traffic condition, the normalized system throughput $S(\tau)$ is defined as the fraction of time the channel is used to successfully transmit payload bits. It is given by:

$$ S(\tau) = \frac{P_s \cdot E[P]}{P_{\text{idle}} \cdot \sigma + P_s \cdot T_s + P_c \cdot T_c} \quad (6) $$
Where $P_{idle}$ is the probability of an idle slot, $P_s$ the probability of a successful transmission and $P_c$ the probability of a collision. For these figures we have:

$$ 
\begin{aligned}
P_{idle} &= (1 - \tau)^n \\
P_s &= n \cdot \tau \cdot (1 - \tau)^{n-1} \\
P_c &= (1 - \theta) \cdot (1 - P_{idle} - P_s)
\end{aligned}
 $$

For IEEE 802.11bd the probability we have:

$$ 
\begin{aligned}
P_{idle} &= (1 - \tau)^n \\
P_s &= n \cdot \tau \cdot (1 - \tau)^{n-1} \\
&\quad + \theta \cdot (1 - (1 - \tau)^n - n \cdot \tau \cdot (1 - \tau)^{n-1}) \\
P_c &= (1 - \theta) \cdot (1 - (1 - \tau)^n - n \cdot \tau \cdot (1 - \tau)^{n-1})
\end{aligned}
 $$

This simplifying assumption allows the impact of enhanced reliability to be isolated at the probability level, without modifying the slot-time structure of Bianchi's framework.

Let us recall the parameters of the Bianchi's model:

* $n$: number of contending stations

* $\tau$: probability that a station transmits in a randomly chosen slot

* $E[P]:$ average payload size measured in time (in ms)

* $T_e$: duration of an empty slot (in ms)

* $T_s$: time the channel is busy due to a successful transmission (in ms)

* $T_c$: time the channel is busy due to a collision (in ms).

In this model, a fraction of collision events is assumed to result in a successful packet reception in IEEE 802.11bd, capturing the effect of advanced PHY-layer mechanisms such as spatial diversity, capture effects, or improved decoding capabilities. For analytical tractability, these successful receptions after collision are assumed to occupy the channel for a duration equal to that of a standard successful transmission $T_s$, rather than a collision duration $T_c$.

## B. Numerical results

Figure 2 illustrates the evolution of the total saturated throughput as a function of the number of contending stations for IEEE 802.11p and IEEE 802.11bd under different values of the parameter $\theta$. As expected, the total throughput decreases as the network density increases due to the growing contention level. However, IEEE 802.11bd consistently achieves higher throughput than IEEE 802.11p for all network sizes. This performance gain becomes more pronounced as $\theta$ increases, reflecting the ability of IEEE 802.11bd to successfully decode a fraction of transmissions even in the presence of collisions. These results highlight the improved robustness of IEEE 802.11bd in dense vehicular scenarios and quantify the throughput benefits brought by enhanced physical-layer reliability mechanisms.

Beyond the absolute throughput gain, these results provide additional insight into the operating regimes where

<figure><img src="image_3.png" /><figcaption>Fig. 2. Normalized throughput in saturation with IEEE 802.11p and IEEE 802.11bd with $\theta = 0.1, 0.3, 0.5$</figcaption></figure>

IEEE 802.11bd brings the largest benefits. The impact of the parameter $\theta$ remains limited in lightly loaded networks, where collisions are rare and both IEEE 802.11p and IEEE 802.11bd operate close to their nominal efficiency. In contrast, in dense scenarios where contention dominates performance, IEEE 802.11bd's ability to successfully recover packets from collisions translates into a significant improvement in spectral efficiency. From a system-level perspective, this behavior indicates that IEEE 802.11bd effectively shifts the main performance bottleneck from collision-induced packet losses toward contention-induced channel access delays, thereby extending the range of network densities over which acceptable throughput can be maintained.

## IV. MODELING MAC LAYER DELAY IN IEEE 802.11P AND IEEE 802.11BD

This section presents an analytical model for the distribution of MAC layer delay in IEEE 802.11p based on terminating renewal processes, as developed in [8]. We extend this model to IEEE 802.11bd by incorporating the improved success probability enabled by PHY/MAC enhancements such as MIMO, higher-order modulation, and cooperative retransmissions.

### A. Terminating Renewal Process for Delay Modeling

We consider a saturated network where each node transmits packets according to the DCF protocol. The time axis is divided into transmission intervals, which may be:

* Empty slot: no node transmits.

* Successful transmission: exactly one node transmits.

* Collision: two or more nodes transmit.

Let $D_{emp}$, $D_{suc}$, and $D_{col}$ denote the durations of these intervals, and let $P_{emp}$, $P_{suc}$, $P_{own}$, and $P_{col}$ be the probabilities
of each event:

$$P_{\text{emp}} = (1 - \tau)^{n-1} \qquad (7)$$

$$P_{\text{suc}} = (n - 1)\tau(1 - \tau)^{n-1} \qquad (8)$$

$$P_{\text{own}} = \tau(1 - \tau)^{n-1} \qquad (9)$$

$$P_{\text{col}} = 1 - P_{\text{emp}} - P_{\text{suc}} - P_{\text{own}} \qquad (10)$$

$$P_{\text{col}} = 1 - (1 - \tau)^{n-1} - n\tau(1 - \tau)^{n-1} \qquad (11)$$

Where $\tau$ is the transmission of the network station. The MAC delay is modeled as a terminating renewal process that ends in a successful transmission by the node under study (event with probability $P_{\text{own}}$). The total delay $M$ is composed of a random sequence of transmission attempts:

$$M = T_1 + T_2 + \dots + T_k + D_{\text{suc}} \qquad (12)$$

where $k$ is geometrically distributed with termination probability $P_{\text{own}}$ and each $T_i$ is independent and has the same improper probability density function $f$ and the probability function $F$:

$$f(T) = \begin{cases} P_{\text{emp}}, & \text{if } T = D_{\text{emp}} \\ P_{\text{suc}}, & \text{if } T = D_{\text{suc}} \\ P_{\text{col}}, & \text{if } T = D_{\text{col}} \end{cases} \\ F_{\text{bd}}(\infty) = 1 - P_{\text{own}}$$

## B. Right-Tail Delay Distribution Approximation

Using renewal theory (see [9]), the right-tail of the delay distribution can be approximated by:

$$P\{M > t\} \approx \frac{1 - F(\infty)}{\chi \cdot \mu} e^{-\chi t} \qquad (13)$$

where $F(\infty) = 1 - P_{\text{own}}$ and the parameter $\chi$ solves:

$$P_{\text{emp}}e^{\chi D_{\text{emp}}} + P_{\text{suc}}e^{\chi D_{\text{suc}}} + P_{\text{col}}e^{\chi D_{\text{col}}} = 1 \qquad (14)$$

and

$$\mu = P_{\text{emp}}D_{\text{emp}}e^{\chi D_{\text{emp}}} + P_{\text{suc}}D_{\text{suc}}e^{\chi D_{\text{suc}}} + P_{\text{col}}D_{\text{col}}e^{\chi D_{\text{col}}} \qquad (15)$$

This expression allows estimation of delay intervals:

$$P\{d \in [a, b]\} = P\{M > a\} - P\{M > b\} \qquad (16)$$

$$P\{d \le c\} = 1 - P\{M > c\} \qquad (17)$$

## C. Extension to IEEE 802.11bd

To account for IEEE 802.11bd's increased probability of success even after collisions, we introduce a tunable parameter $\theta \in [0, 1]$, which models the probability that a packet is successfully decoded despite a collision.

We modify the transition probabilities as follows:

$$P_{\text{emp}}^{\text{bd}} = (1 - \tau)^{n-1} \qquad (18)$$

$$P_{\text{suc}}^{\text{bd}} = (n - 1)\tau(1 - \tau)^{n-1} + \theta * (1 - (1 - \tau)^{n-1} - n\tau(1 - \tau)^{n-1}) \qquad (19)$$

$$P_{\text{col}}^{\text{bd}} = (1 - \theta) * (1 - (1 - \tau)^{n-1} - n\tau(1 - \tau)^{n-1}) \qquad (20)$$

Substituting these into the equations for $\chi$ and $\mu$ allows us to derive the adjusted delay distribution for IEEE 802.11bd:

$$P\{M_{\text{bd}} > t\} \approx \frac{1 - F_{\text{bd}}(\infty)}{\chi_{\text{bd}} \cdot \mu_{\text{bd}}} e^{-\chi_{\text{bd}}t} \qquad (21)$$

with

$$F_{\text{bd}}(\infty) = 1 - P_{\text{own}}^{\text{bd}}$$

<figure><img src="image_4.png" /><figcaption>Fig. 3. Delay distribution in saturation with IEEE 802.11p and IEEE 802.11bd with $\theta = 0.1, 0.3, 0.5$</figcaption></figure>

## D. Numerical results

We use the following numerical figures $m = 5$, $W_0 = 32$, $T_e = 0.013$ ms, $T_s = 0.806$ ms, $T_c = 0.75$ ms.

Figure 3 presents the MAC layer delay distribution in a saturated network for IEEE 802.11p and IEEE 802.11bd, with various values of the tunable parameter $\theta$ ($\theta = 0.1, 0.3, 0.5$). This parameter captures the probability of successful packet reception despite collisions in IEEE 802.11bd, thanks to advanced physical layer techniques like MIMO and retransmission diversity.

As shown in the figure, IEEE 802.11bd does not reduce the tail of the delay distribution compared to IEEE 802.11p. When $\theta$ increases, the probability of long delays increases slowly. For instance, with $\theta = 0$ (i.e for IEEE 802.11p) the proportion of packets experiencing a delay greater than 20 ms is 0.393, with $\theta = 0.1$, the proportion of packets experiencing a delay greater than 20 ms is 0.405 with $\theta = 0.3$, the proportion of packets experiencing a delay greater than 20 ms is 0.443, with $\theta = 0.5$, the proportion of packets experiencing a delay greater than 20 ms is 0.516. However, we must note that we are in a saturation model and as seen in the previous section the delivered throughput increases in IEEE 802.11bd with $\theta$. Thus if the throughput increases, the delays also increase. Thus for the same input traffic, IEEE 802.11bd has inferior delays.

It is important to emphasize that these delay results are obtained under saturated traffic conditions, which represent a pessimistic operating point for vehicular networks. In such a regime, any increase in transmission efficiency directly
increases the channel load, leading to higher contention and
longer medium access delays. This explains why improving
the probability of successful decoding through higher values
of θ does not reduce, and may even increase, the tail of the
delay distribution under saturation.

In practical V2X deployments, however, networks are typi-
cally operated below saturation, particularly for safety-related
applications where packet generation rates are regulated. In
these non-saturated regimes, the improved reliability and re-
duced packet loss offered by IEEE 802.11bd are expected
to translate into lower effective delays for a given offered
traffic load. Consequently, the saturation-based delay analysis
presented here should be interpreted as highlighting a fun-
damental throughput-delay trade-off rather than as a direct
prediction of end-to-end latency performance in real-world
deployments.

V. CONCLUSION AND FUTURE WORK

In this paper, we proposed an analytical framework to
compare the performance of IEEE 802.11p and its successor
IEEE 802.11bd under saturated traffic conditions. Building
upon Bianchi's well-established Markov chain model, we
introduced a simple yet expressive modification that cap-
tures the enhanced reliability mechanisms of IEEE 802.11bd
through a tunable parameter θ, representing the probability
of successful packet decoding in the presence of collisions.
This abstraction allows advanced physical-layer features such
as spatial diversity, improved coding, or capture effects to
be incorporated into a tractable MAC-layer analysis without
altering the fundamental CSMA/CA operation.

The analytical results highlight that IEEE 802.11bd signif-
icantly mitigates the negative impact of collisions compared
to IEEE 802.11p. In particular, the throughput analysis shows
that, for all network densities, IEEE 802.11bd achieves higher
saturated throughput, with gains that increase as θ grows. This
confirms that enhanced decoding capabilities can effectively
improve spectrum efficiency in dense vehicular networks,
where contention is a major limiting factor. The proposed
model thus provides an intuitive and quantitative explanation
of how IEEE 802.11bd leverages physical-layer robustness
to outperform legacy IEEE 802.11p in terms of delivered
throughput.

Beyond throughput, we extended an existing terminating re-
newal process model to study the MAC-layer delay distribution
under saturation. This delay-oriented analysis complements the
throughput results by offering insight into latency behavior,
which is a critical metric for safety-related V2X applications.
The analytical expressions derived for the right-tail of the
delay distribution show that, under saturated conditions, in-
creasing θ leads to a higher probability of long delays. This
behavior stems from the fact that improved decoding success
increases the effective load carried by the channel, thereby
intensifying contention and queueing effects at the MAC layer.

These results underline an important trade-off: while
IEEE 802.11bd improves throughput by successfully recov-

ering transmissions that would otherwise be lost due to colli-
sions, this improvement does not automatically translate into
reduced delays under saturation. On the contrary, when the
network operates at its maximum capacity, higher throughput
may be accompanied by longer delays. This observation em-
phasizes that throughput and delay must be jointly considered
when evaluating V2X communication technologies. In practi-
cal deployments, however, networks are rarely operated at full
saturation, and for a fixed offered traffic load, the improved
efficiency of IEEE 802.11bd is expected to reduce both packet
loss and latency compared to IEEE 802.11p.

The proposed analytical framework is intentionally sim-
plified in order to preserve tractability and provide clear
insights into the fundamental mechanisms at play. Several
extensions can be envisioned as future work. First, a more
detailed Markov chain model could explicitly account for
IEEE 802.11bd-specific features such as multiple retransmis-
sion opportunities, channel bonding, or adaptive modulation
and coding schemes. Second, the parameter θ could be linked
to physical-layer signal-to-interference-plus-noise ratio (SINR)
distributions, enabling a tighter coupling between PHY and
MAC layers. Finally, validating the analytical predictions
through detailed simulations or experimental measurements
in realistic vehicular scenarios would further strengthen the
conclusions of this study.

REFERENCES

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[2] C. F. Mecklenbräuker et al., "Vehicular channel characterization and its implications for wireless system design and performance," *Proceedings of the IEEE*, vol. 99, no. 7, pp. 1189-1212, 2011.

[3] G. Bianchi, "Performance analysis of the ieee 802.11 distributed coordination function," *IEEE Journal on Selected Areas in Communications*, vol. 18, no. 3, pp. 535-547, 2000.

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