High-Level System Design of IEEE 802.11b Standard-Compliant Link Layer for MATLAB-Based SDR

Subramanian, Ramanathan; Drozdenko, Benjamin; Doyle, Eric; Ahmed, Rameez; Leeser, Miriam; Chowdhury, Kaushik R.

doi:10.1109/access.2016.2553671

Cited by 5 publications

(4 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The sample size for every group was calculated using a G Power calculator having 80% pretest power, an alpha error of 0.95, a threshold value of 0.05, and a 86% confidence level. Accuracies of both models are tested with a sample size of 10 using Matlab (Subramanian et al 2016).…”

Section: Methodsmentioning

confidence: 99%

Effective Classification of Colon Cancer using Resnet-18 in Comparison with Squeezenet

2022

pnr

View full text Add to dashboard Cite

The work aims to find out a better way to perform colon cancer identification with the help of Resnet-18 algorithm in comparison with a Squeezenet algorithm to maximize the accuracy in finding rather than the existing method of prediction. Materials and Methods: A collection of 30 samples were picked for consideration; group 1 visualizing Resnet-18 classifier algorithm and finally group 2 is responsible for the Squeezenet algorithm. Thus G power calculation is done with a power of 80.5 and the alpha value is equivalent to 0.061. Results: When compared to the Squeezenet algorithm, the Resnet-18 classifier algorithm has attained an accuracy of 86.5060 % and 0.32754 which is somewhat greater than the existing method. ( Squeezenet algorithm attained an accuracy of 83.5433% and 0.28975) respectively. Conclusion:From the above statement it is evident that the Resnet-18 algorithm would be a better choice for predicting colon cancer and it is more effective.

show abstract

Section: Methodsmentioning

confidence: 99%

Effective Classification of Colon Cancer using Resnet-18 in Comparison with Squeezenet

2022

pnr

View full text Add to dashboard Cite

show abstract

“…However, they abstain from addressing the specific considerations required by SDR platforms based on the requirement of wireless technologies. This problem is slightly addressed by other researchers and developers in two different perspectives, by designing a custom SDR architecture suited to a specific implementation such as [20]- [22], and/or providing list of recommended requirements to implement a certain wireless technology. Regarding the latter case, the recommendations are usually provided by SDR platform software implementations such as Software Radio Systems (SRS) [14], OpenAirInterface Software (OAI) [23], gr-IEEE-802.15.4 [15], gr-LoRa [24], etc.…”

Section: Introductionmentioning

confidence: 99%

Software Defined Radio Platforms for Wireless Technologies

et al. 2022

View full text Add to dashboard Cite

Wireless connectivity standards have been developed to meet the requirements of various applications. To support a wireless standard, a wireless transceiver should be equipped with a Radio Frequency (RF) transceiver. Traditional RF transceivers are designed and implemented on a radio chip or an embedded module in a System-on-a-Chip (SoC), ensuring small size, high performance, low power consumption, and cost. However, this traditional implementation design limits directly or indirectly the programmability and flexibility of the RF transceivers. An alternative solution is to implement RF transceivers using Software Defined Radio (SDR) platforms. In the market, SDR platform hardware exists with different configurations, performance, cost, size, etc., making it hard to select the minimum SDR platform necessary to satisfy the wireless standard requirements. This paper aims to provide a list of wellknown General Purpose Processor (GPP) based SDR platforms satisfying the minimum specifications of selected wireless standards. To this end, we first review the characteristics of selected wireless technologies. Then, we investigate existing SDR platform architecture and their maximal performance in terms of the frequency range, bandwidth, symbol rate, bitrate, and latency support. Finally, we intersect the wireless standard requirements with the corresponding SDR platform parameters and provide a list of GPP-based SDR platforms for some existing wireless technology implementations. While investigations related to frequency, bandwidth, symbol rate and bitrate are supported by theoretical results, latency is obtained from experiments by benchmarking existing implementations.

show abstract

“…Software-defined radio (SDR) is a tool that is primarily intended to be used to test and prototype various communication applications such as wireless communications and the Global Navigation Satellite System (GNSS). For example, these include mobile telecommunication [ 1 , 2 ], multi-static multiple-input and multiple-output (MIMO) communication [ 3 , 4 , 5 ], Wi-Fi [ 6 ], characterizing radio-frequency identification (RFID) tags [ 7 , 8 ], prototyping a global positioning systems (GPS) receiver [ 9 , 10 ], locating satellites [ 11 ], and indoor positioning [ 12 ]. The use of SDR is becoming popular because of the fully digital in-phase and quadrature (I/Q) interface, which provides flexibility in signal generation and postprocessing of received signals.…”

Section: Introductionmentioning

confidence: 99%

A Local Oscillator Phase Compensation Technique for Ultra-Wideband Stepped-Frequency Continuous Wave Radar Based on a Low-Cost Software-Defined Radio

Takahashi

Miwa

2021

Sensors

View full text Add to dashboard Cite

The paper discusses a way to configure a stepped-frequency continuous wave (SFCW) radar using a low-cost software-defined radio (SDR). The most of high-end SDRs offer multiple transmitter (TX) and receiver (RX) channels, one of which can be used as the reference channel for compensating the initial phases of TX and RX local oscillator (LO) signals. It is same as how commercial vector network analyzers (VNAs) compensate for the LO initial phase. These SDRs can thus acquire phase-coherent in-phase and quadrature (I/Q) data without additional components and an SFCW radar can be easily configured. On the other hand, low-cost SDRs typically have only one transmitter and receiver. Therefore, the LO initial phase has to be compensated and the phases of the received I/Q signals have to be retrieved, preferably without employing an additional receiver and components to retain the system low-cost and simple. The present paper illustrates that the difference between the phases of TX and RX LO signals varies when the LO frequency is changed because of the timing of the commencement of the mixing. The paper then proposes a technique to compensate for the LO initial phases using the internal RF loopback of the transceiver chip and to reconstruct a pulse, which requires two streaming: one for the device under test (DUT) channel and the other for the internal RF loopback channel. The effect of the LO initial phase and the proposed method for the compensation are demonstrated by experiments at a single frequency and sweeping frequency, respectively. The results show that the proposed method can compensate for the LO initial phases and ultra-wideband (UWB) pulses can be reconstructed correctly from the data sampled by a low-cost SDR.

show abstract

High-Level System Design of IEEE 802.11b Standard-Compliant Link Layer for MATLAB-Based SDR

Cited by 5 publications

References 16 publications

Effective Classification of Colon Cancer using Resnet-18 in Comparison with Squeezenet

Effective Classification of Colon Cancer using Resnet-18 in Comparison with Squeezenet

Software Defined Radio Platforms for Wireless Technologies

A Local Oscillator Phase Compensation Technique for Ultra-Wideband Stepped-Frequency Continuous Wave Radar Based on a Low-Cost Software-Defined Radio

Contact Info

Product

Resources

About