A Summative Comparison of Blind Channel Estimation Techniques for Orthogonal Frequency Division Multiplexing Systems

The OFDM techniquei.e. Orthogonal frequency division multiplexing has become prominent in wireless communication since its instruction in 1950’s due to its feature of combating the multipath fading and other losses. In an OFDM system, a large number of orthogonal, overlapping, narrow band subchannels or subcarriers, transmitted in parallel, divide the available transmission bandwidth. The separation of the subcarriers is theoretically optimal such that there is a very compact spectral utilization. This paper reviewed the possible approaches for blind channel estimation in the light of the improved performance in terms of speed of convergence and complexity. There were various researches which adopted the ways for channel estimation for Blind, Semi Blind and trained channel estimators and detectors. Various ways of channel estimation such as Subspace, iteration based, LMSE or MSE based (using statistical methods), SDR, Maximum likelihood approach, cyclostationarity, Redundancy and Cyclic prefix based. The paper reviewed all the above approaches in order to summarize the outcomes of approaches aimed at optimum performance for channel estimation in OFDM system

Development And Implementation Of Improved Coded OFDM System Using SDR Platform

he increasing demand for high speed wireless connectivity at low cost poses new challenges for communication system designers, to implement solutions that increase the data rate by utilizing the limited radio resources more efficiently at a low additional complexity. Adaptive Coding and Modulation (ACM) exploits the flexibility of channel coding and constellation in Orthogonal Frequency Division Multiplexing (OFDM) to obtain higher data rates. This technique employs multiple modulation and coding schemes to instantaneously adapt to the variations in the channel Signal to Noise Ratio (SNR), thus maximizing the system throughput and improving Bit Error Rate (BER) performance. On the other hand, OFDM system suffers from inter-symbol interference (ISI), especially in mobile communication environments. This problem may be tackled by increasing the individual symbol duration for each subcarrier together with the use of guard time. Nevertheless, this does not solve the problem completely in multipath fading channel, because all subcarriers will arrive at the receiver with different amplitudes. Unfortunately, some subcarriers may be completely lost because of deep fades. Hence even though most subcarriers may be detected without errors, the overall BER will be largely dominated by a few subcarriers with bad SNR. To eliminate this problem, OFDM based systems usually employ a special technique like error correction coding (ECC). Various coding methods are adopted by many standards to mitigate the effects of frequency selective channel which causes bit errors to occur in bur

Enhancing system performance through objective feature scoring of multiple persons' breathing using non-contact RF approach

Breathing monitoring is an efficient way of human health sensing and predicting numerous diseases. Various contact and non-contact-based methods are discussed in the literature for breathing monitoring. Radio frequency (RF)-based breathing monitoring has recently gained enormous popularity among non-contact methods. This method eliminates privacy concerns and the need for users to carry a device. In addition, such methods can reduce stress on healthcare facilities by providing intelligent digital health technologies. These intelligent digital technologies utilize a machine learning (ML)-based system for classifying breathing abnormalities. Despite advances in ML-based systems, the increasing dimensionality of data poses a significant challenge, as unrelated features can significantly impact the developed system’s performance. Optimal feature scoring may appear to be a viable solution to this problem, as it has the potential to improve system performance significantly. Initially, in this study, software-defined radio (SDR) and RF sensing techniques were used to develop a breathing monitoring system. Minute variations in wireless channel state information (CSI) due to breathing movement were used to detect breathing abnormalities in breathing patterns. Furthermore, ML algorithms intelligently classified breathing abnormalities in single and multiple-person scenarios. The results were validated by referencing a wearable sensor. Finally, optimal feature scoring was used to improve the developed system’s performance in terms of accuracy, training time, and prediction speed. The results showed that optimal feature scoring can help achieve maximum accuracy of up to 93.8% and 91.7% for single-person and multi-person scenarios, respectively

Review of Recent Trends

This work was partially supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Centre (CENTRO 2020) of the Portugal 2020 framework, through projects SOCA (CENTRO-01-0145-FEDER-000010) and ORCIP (CENTRO-01-0145-FEDER-022141). Fernando P. Guiomar acknowledges a fellowship from “la Caixa” Foundation (ID100010434), code LCF/BQ/PR20/11770015. Houda Harkat acknowledges the financial support of the Programmatic Financing of the CTS R&D Unit (UIDP/00066/2020).MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.publishersversionpublishe

Software Defined Radio Implementation Of Ds-Cdma In Inter-Satellite Communications For Small Satellites

The increased usage of CubeSats recently has changed the communication philosophy from long-range point-to-point propagations to a multi-hop network of small orbiting nodes. Separating system tasks into many dispersed satellites can increase system survivability, versatility, configurability, adaptability, and autonomy. Inter-satellite links (ISL) enable the satellites to exchange information and share resources while reducing the traffic load to the ground. Establishment and stability of the ISL are impacted by factors such as the satellite orbit and attitude, antenna configuration, constellation topology, mobility, and link range. Software Defined Radio (SDR) is beginning to be heavily used in small satellite communications for applications such as base stations. A software-defined radio is a software program that does the functionality of a hardware system. The digital signal processing blocks are incorporated into the software giving it more flexibility and modulation. With this, the idea of a remote upgrade from the ground as well as the potential to accommodate new applications and future services without hardware changes is very promising. Realizing this, my idea is to create an inter-satellite link using software defined radio. The advantages of this are higher data rates, modification of operating frequencies, possibility of reaching higher frequency bands for higher throughputs, flexible modulation, demodulation and encoding schemes, and ground modifications. However, there are several challenges in utilizing the software-defined radio to create an inter-satellite link communication for small satellites. In this paper, we designed and implemented a multi-user inter-satellite communication network using SDRs, where Code Division Multiple Access (CDMA) technique is utilized to manage the multiple accesses to shared communication channel among the satellites. This model can be easily reconfigured to support any encoding/decoding, modulation, and other signal processing schemes