# Performance Analysis of a Novel TCP Protocol Algorithm Adapted to Wireless Networks
## 1 Introduction
This protocol fairly estimates the bandwidth to set the CWND and the _ssthresh_ after three DUPAC or after a timeout. The protocol was simulated by ns-2, where the \(\theta\) gain over TCP Westwood was 17 percent at 0.01 BER and 542% over TCP New-Reno at 0.5 BER. Finally, another wireless link problem to be addressed is the Retransmission Timeout (RTO) which is calculated based on the Round-Trip Time (RTT), which is fluctuating in wireless networks. This RTT dependence can be appreciated on in-door environments, where \(\theta\) unbalances, hidden terminals problems, and interference among Basic Service Sets frequently occur. As a solution, in [12], a MAC layer contention window control is proposed using an analytical model of nonlinear equations, achieving a fair \(\theta\) distribution with a confidence interval of 99.98% at a 2 Mb/s bit rate. Several solutions for wired-cum-wireless network improvement with a wireless local retransmission approach have been also proposed, for example, in [13], the snoop protocol caches unacknowledged packets from the fixed host at the Base Station (BS) and performs local retransmissions across the wireless link. For a wireless link BER of over \(5\times 10^{-7}\), the snoop protocol achieves a \(\overline{\theta}\) improvement of 1 to 20 times than TCP Reno for data transfer from the fixed host to the MH, requiring modifications at the BS and the MH. In [14], a TCP extension called Delayed Congestion Response TCP protocol (TCP-DCR) was proposed. Such protocol delays the fast retransmit/recovery algorithm when the sender receives the first DUPAC by starting a delayed response timer in order to allow a link level retransmission at the BS to recover a lost packet. With some modifications at the sender host, TCP-DCR reaches better \(\theta\) than TCP-SACK for several BER values. Meanwhile, in [15], the authors propose a trend topic in communications by using machine learning based loss discrimination algorithm (ML-LDA) for wireless TCP congestion control. ML-LDA learns how to distinguish packet losses due to congestion and wireless channel environment using multi-layer perceptron (MLP). Based on the learning results, the congestion control classifies the cause of losses and does not reduce congestion window in case of random losses. The algorithm was implemented in Linux kernel and configured a testbed where packet loss occurs randomly. They compared the experimental results with TCP-Renoand TCP-Westwood and showed that the proposed ML-LDA has 98% packet loss classification accuracy in wireless channel environments, and average throughput is greatly improved compared to the others congestion controls. In this context, the aim of this paper is to describe the development of a novel simple TCP protocol algorithm adapted to wireless networks. Specifically, we address improvements in the wireless TCP. In this paper, we will consider all stages related to performance evaluation, including a mathematical analysis, configuring our proposal by modifying the linux kernel, emulations, and finally testbed analysis in real scenarios. Our primary hypothesis is that by inserting a negative acknowledgment (NACK) flag inside the TCP header, naming this TCP modification as \"TCP-NACK\", we will prevent the misinterpretation of PL due to channel instability, as well as PL due to congestion, thus reaching a better performance. In this sense, we consider the ELN concept of retransmitting corrupted packets without the CWND reduction. The rest of the paper is organized as follows: In Section 2, we describe the methods and materials used for TCP-NACK design, emulation, and evaluation. Section 3 presents the experimentation process and how the results were obtained. Section 4 presents the discussion of the results when compared to generic TCP algorithms. Finally, our conclusion and future works are presented in Section 5.