D-Fi is a novel Wi-Fi PHY/MAC protocol that exploits frequency diversity while maintaining protocol efficiency with minimal overhead. It achieves this by leveraging an OFDM-based Bloom filter to synergistically integrate channel quality estimation and contention-based channel allocation. D-Fi resolves false positives from the Bloom filter using machine learning and explores new channel quality using a decentralized multi-armed bandit algorithm. Experiments show D-Fi provides up to 3x throughput improvement over existing solutions.

1. Frequency Diversity-Aware Wi-Fi Using OFDM-Based Bloom Filters
Abstract:
With the increasing move towards wide band operation in recent Wi-Fi
networks, the frequency diversity awareness has become critical for
throughput optimization. To exploit frequency diversity in Wi-Fi channels,
the access point should measure the channel quality and coordinate the
channel contention for all the stations. However, there is a tradeoff
between achieving the frequency diversity gain and sustaining protocol
efficiency because the channel estimation and coordination consume time
and frequency resource that ideally should be used for data transfer. In this
paper, we present Diversity-aware Wi-Fi (D-Fi), a novel PHY/MAC
protocol, that efficiently exploits frequency diversity. In particular, D-Fi
leverages an OFDM-based Bloom filter that synergistically integrates two
operations: (i) the channel quality estimation and (ii) the contention based
channel allocation. D-Fi also employs a machine learning (ML) method to
resolve the false-positive ambiguity caused by the Bloom filter.
Furthermore, we develop a decentralized algorithm, called K_-greedy,
based on the Multi-Armed Bandit (MAB) framework, so that it achieves
sub-optimal performance by studying the gain for exploring new channel
quality information. We implement the prototype of D-Fi on the USRP/
GNURadio to validate the feasibility of our work. The experiments and

2. trace-driven simulations show that D-Fi provides up to 3 _ throughput
improvement compared to the existing solutions.
Existing System:
The spatial and temporal diversities, the signals transmitted over a wide
frequency band experience independent fluctuations across different
frequencies. This phenomenon is generally caused by the frequency
selective fading and frequency dependent attenuation.
Further, the frequency diversity aware schemes usually require the
coordination of the channel access requests from STAs based on the
channel estimation results so as to opportunistically harness the frequency
diversity, which requires the additional corresponding protocol overhead
In short; there is a strict tradeoff between frequency diversity gains and
protocol efficiency.
Proposed System:
Although a variety of approaches have been recently proposed in Wi-Fi
networks to achieve frequency diversity awareness none of them explore
achieving two objectives, i.e., achieving both frequency diversity and
protocol efficiency, simultaneously.
Most previous work emphasizes mainly on one side; exploiting frequency
diversity with additional channel estimation costs or improving only the

3. protocol efficiency (e.g., reducing channel contention cost) by operating at
the frequency domain.
we present Diversity-aware Wi-Fi (D-Fi), a novel Wi-Fi PHY/MAC protocol
that exploits frequency diversity while sustaining protocol efficiency with
minimum channel estimation and allocation cost. Specifically, D-Fi
synergistically integrates channel information estimation with the channel
contention resolution by leveraging an OFDM-based Bloom filter. D-Fi
does not require a dedicated channel estimation mechanism.
Hardware Requirements:
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• RAM : 256 Mb.
Software Requirements:
• Operating system : - Windows XP.
• Front End : - JSP
• Back End : - SQL Server

4. Software Requirements:
• Operating system : - Windows XP.
• Front End : - .Net
• Back End : - SQL Server