arXiv subjects

Ali E. Pusane

Publications and source records attributed to Ali E. Pusane.

12 recordsLinked to original sources

arXiv2025

Interference Modulation: A Novel Technique for Low-Rate and Power Efficient Multiple Access

The majority of spatial signal processing techniques focus on increasing the total system capacity and providing high data rates for intended user(s). Unlike the existing studies, this paper introduces a novel interference modulation method that exploits the correlation between wireless channels to enable low-data-rate transmission towards additional users with a minimal power allocation. The proposed method changes the interference power at specific channels to modulate a low-rate on-off keying signal. This is achieved by appropriately setting the radiation pattern of front-end components of a transmitter, i.e., analog beamforming weights or metasurface configuration. The paper investigates theoretical performance limits and analyzes the efficiency in terms of sum rate. Bit error rate simulation results are closely matched with theoretical findings. The initial findings indicate that the proposed technique can be instrumental in providing reduced capability communication using minimal power consumption in 6G networks.

eess.SP↗

arXiv2024

RF Chain-Free mmWave Transmission: Modeling and Experimental Verification

The utilization of millimeter wave frequency bands is expected to become prevalent in the following communication systems. However, generating and transmitting communication signals over these frequencies is not as straightforward as in sub-6 GHz frequencies due to complex transceiver structures. As an alternative to conventional transmitter architectures, this paper investigates the implementation of time-modulated arrays to effectively modulate and transmit high-quality communication signals at millimeter wave frequencies. By exploiting the array structures and analog beamformers, which are the fundamental components of millimeter wave transmitters, secure and low-cost transmission can be achieved. Though, harmonics of theoretically infinite bandwidth arise as a fundamental problem in this approach. Thus, this paper presents a frequency analysis tool for the time-modulated arrays with hardware impairments and shows how controlling the sampling period can reduce the harmonics. Furthermore, the derived results are experimentally verified at 25 GHz with two important remarks. First, the phase error of received signals can be reduced by 32% using the proposed architecture. Second, the harmonics can be significantly suppressed by the correct choice of sampling period for the given hardware.

eess.SP↗

arXiv2023

A Novel Blind Adaptive Beamformer with Robustness against Mutual Coupling and Miscalibration Effects

Beamforming techniques utilized either at the transmitter or the receiver terminals have achieved superior quality-of-service performances from both the multi-antenna wireless communications systems, communications intelligence and radar target detection perspectives. Despite the overwhelming advantages in ideal operating conditions, beamforming approaches have been shown to face substantial performance degradations due to unknown mutual coupling effects and miscalibrated array elements. As a promising solution, blind beamformers have been proposed as a class of receiver beamformers that do not require a reference signal to operate. In this paper, a novel gradient-based blind beamformer is introduced with the aim of mitigating the deteriorating effects of unknown mutual coupling or miscalibration effects. The proposed approach is shown to find the optimal weights in different antenna array configurations in the presence of several unknown imperfections (e.g., mutual coupling effects, miscalibration effects due to gain and phase variations, inaccurate antenna positions). By providing numerical results related to the proposed algorithm for different array configurations, and bench-marking with the other existing approaches, the proposed scheme has been shown to achieve superior performance in many aspects. Additionally, a measurement-based analysis has been included with validation purposes.

eess.SP↗

arXiv2021

Analytical Investigation of Long-time Diffusion Dynamics in a Synaptic Channel with Glial Cells

In this letter, we first derive the analytical channel impulse response for a cylindrical synaptic channel surrounded by glial cells and validate it with particle-based simulations. Afterwards, we provide an accurate analytical approximation for the long-time decay rate of the channel impulse response by employing Taylor expansion to the characteristic equations that determine the decay rates of the system. We validate our approximation by comparing it with the numerical decay rate obtained from the characteristic equation. Overall, we provide a fully analytical description for the long-time behavior of synaptic diffusion, e.g., the clean-up processes inside the channel after communication has long concluded.

q-bio.NC↗

arXiv2021

MIMO Operations in Molecular Communications: Theory, Prototypes, and Open Challenges

The Internet of Bio-nano Things is a significant development for next generation communication technologies. Because conventional wireless communication technologies face challenges in realizing new applications (e.g., in-body area networks for health monitoring) and necessitate the substitution of information carriers, researchers have shifted their interest to molecular communications (MC). Although remarkable progress has been made in this field over the last decade, advances have been far from acceptable for the achievement of its application objectives. A crucial problem of MC is the low data rate and high error rate inherent in particle dynamics specifications, in contrast to wave-based conventional communications. Therefore, it is important to investigate the resources by which MC can obtain additional information paths and provide strategies to exploit these resources. This study aims to examine techniques involving resource aggregation and exploitation to provide prospective directions for future progress in MC. In particular, we focus on state-of-the-art studies on multiple-input multiple-output (MIMO) systems. We discuss the possible advantages of applying MIMO to various MC system models. Furthermore, we survey various studies that aimed to achieve MIMO gains for the respective models, from theoretical background to prototypes. Finally, we conclude this study by summarizing the challenges that need to be addressed.

cs.IT↗

arXiv2014

ISI Mitigation Techniques in Molecular Communication

Molecular communication is a new field of communication where molecules are used to transfer information. Among the proposed methods, molecular communication via diffusion (MCvD) is particularly effective. One of the main challenges in MCvD is the intersymbol interference (ISI), which inhibits communication at high data rates. Furthermore, at the nano scale, energy efficiency becomes an essential problem. Before addressing these problems, a pre-determined threshold for the received signal must be calculated to make a decision. In this paper, an analytical technique is proposed to determine the optimum threshold, whereas in the literature, these thresholds are generally calculated empirically. Since the main goal of this paper is to build an MCvD system suitable for operating at high data rates without sacrificing quality, new modulation and filtering techniques are proposed to decrease the effects of ISI and enhance energy efficiency. As a transmitter-based solution, a modulation technique for MCvD, molecular transition shift keying (MTSK), is proposed in order to increase the data rate via suppressing the ISI. Furthermore, for energy efficiency, a power adjustment technique that utilizes the residual molecules is proposed. Finally, as a receiver-based solution, a new energy efficient decision feedback filter (DFF) is proposed as a substitute for the decoders such as minimum mean squared error (MMSE) and decision feedback equalizer (DFE). The error performance of DFF and MMSE equalizers are compared in terms of bit error rates, and it is concluded that DFF may be more advantageous when energy efficiency is concerned, due to its lower computational complexity.

cs.ET↗

arXiv2014

Arrival Modeling and Error Analysis for Molecular Communication via Diffusion with Drift

The arrival of molecules in molecular communication via diffusion (MCvD) is a counting process, exhibiting by its nature binomial distribution. Even if the binomial process describes well the arrival of molecules, when considering consecutively sent symbols, the process struggles to work with the binomial cumulative distribution function (CDF). Therefore, in the literature, Poisson and Gaussian approximations of the binomial distribution are used. In this paper, we analyze these two approximations of the binomial model of the arrival process in MCvD with drift. Considering the distance, drift velocity, and the number of emitted molecules, we investigate the regions in which either Poisson or Gaussian model is better in terms of root mean squared error (RMSE) of the CDFs; we confirm the boundaries of the region via numerical simulations. Moreover, we derive the error probabilities for continuous communication and analyze which model approximates it more accurately.

cs.ET↗

arXiv2011

Exact Free Distance and Trapping Set Growth Rates for LDPC Convolutional Codes

Ensembles of (J,K)-regular low-density parity-check convolutional (LDPCC) codes are known to be asymptotically good, in the sense that the minimum free distance grows linearly with the constraint length. In this paper, we use a protograph-based analysis of terminated LDPCC codes to obtain an upper bound on the free distance growth rate of ensembles of periodically time-varying LDPCC codes. This bound is compared to a lower bound and evaluated numerically. It is found that, for a sufficiently large period, the bounds coincide. This approach is then extended to obtain bounds on the trapping set numbers, which define the size of the smallest, non-empty trapping sets, for these asymptotically good, periodically time-varying LDPCC code ensembles.

cs.IT↗

arXiv2010

Deriving Good LDPC Convolutional Codes from LDPC Block Codes

Low-density parity-check (LDPC) convolutional codes are capable of achieving excellent performance with low encoding and decoding complexity. In this paper we discuss several graph-cover-based methods for deriving families of time-invariant and time-varying LDPC convolutional codes from LDPC block codes and show how earlier proposed LDPC convolutional code constructions can be presented within this framework. Some of the constructed convolutional codes significantly outperform the underlying LDPC block codes. We investigate some possible reasons for this "convolutional gain," and we also discuss the --- mostly moderate --- decoder cost increase that is incurred by going from LDPC block to LDPC convolutional codes.

cs.IT↗

arXiv2008

Asymptotically Good LDPC Convolutional Codes Based on Protographs

LDPC convolutional codes have been shown to be capable of achieving the same capacity-approaching performance as LDPC block codes with iterative message-passing decoding. In this paper, asymptotic methods are used to calculate a lower bound on the free distance for several ensembles of asymptotically good protograph-based LDPC convolutional codes. Further, we show that the free distance to constraint length ratio of the LDPC convolutional codes exceeds the minimum distance to block length ratio of corresponding LDPC block codes.

cs.IT↗

arXiv2008

Free Distance Bounds for Protograph-Based Regular LDPC Convolutional Codes

In this paper asymptotic methods are used to form lower bounds on the free distance to constraint length ratio of several ensembles of regular, asymptotically good, protograph-based LDPC convolutional codes. In particular, we show that the free distance to constraint length ratio of the regular LDPC convolutional codes exceeds that of the minimum distance to block length ratio of the corresponding LDPC block codes.

cs.IT↗

arXiv2006

Pseudo-Codeword Performance Analysis for LDPC Convolutional Codes

Message-passing iterative decoders for low-density parity-check (LDPC) block codes are known to be subject to decoding failures due to so-called pseudo-codewords. These failures can cause the large signal-to-noise ratio performance of message-passing iterative decoding to be worse than that predicted by the maximum-likelihood decoding union bound. In this paper we address the pseudo-codeword problem from the convolutional-code perspective. In particular, we compare the performance of LDPC convolutional codes with that of their ``wrapped'' quasi-cyclic block versions and we show that the minimum pseudo-weight of an LDPC convolutional code is at least as large as the minimum pseudo-weight of an underlying quasi-cyclic code. This result, which parallels a well-known relationship between the minimum Hamming weight of convolutional codes and the minimum Hamming weight of their quasi-cyclic counterparts, is due to the fact that every pseudo-codeword in the convolutional code induces a pseudo-codeword in the block code with pseudo-weight no larger than that of the convolutional code's pseudo-codeword. This difference in the weight spectra leads to improved performance at low-to-moderate signal-to-noise ratios for the convolutional code, a conclusion supported by simulation results.

cs.IT↗