Multicarrier Modulation

Unequal error protection is the key to future transport of multimedia data. The paper presents an overview of some new approaches realizing UEP properties in physical transport, especially multicarrier modulation, or with LDPC and Turbo codes. For multicarrier modulation, a UEP bit-loading method is described allowing for an arbitrary number of classes, arbitrary SNR margins between the classes and arbitrary number of bits per class. In Turbo coding, pruning, as a counterpart of puncturing is presented for more flexible bit-rate adaptations. Pruning is also the tool that leads to a construction approach for check-irregular LDPC codes with UEP properties.

Tensor decompositions provide a natural modeling framework for modern wireless communication and array processing systems. This survey presents a physicsdriven perspective on structured CP/PARAFAC models, identifiability conditions, and constrained factorizations. We emphasize how propagation mechanisms lead to multilinear separability, how diversity across modes ensures identifiability, and how reconfigurable architectures introduce controllable tensor dimensions. The discussion bridges wireless channel estimation and radar parameter recovery under a unified multilinear viewpoint.

This report provides a concise review of tensor decomposition models in wireless communications and array processing. Emphasis is placed on physics-driven tensorization, structured CP/PARAFAC models, identifiability conditions, RIS-induced higher-order tensor models, and practical algorithmic considerations. We highlight the interplay between propagation physics, multilinear algebra, and estimation theory.

Massive Multiple Input Multiple Output (MIMO) system has gathered lately a huge interest from researchers and it has been known as a backbone technology for the 5th generation because it can greatly improve the capacity of wireless communication and it can potentially provide energy efficiency and security. Before ensuring the full advantages, massive MIMO system has to overcome many challenges. One of them is to accurate an exact estimation of the Channel Impulse response (CIR) between each transmit-receive antenna pair. The other problem arises when implementing such a system in presence of High Power Amplifiers (HPA) which imposes a nonlinear distortion on the transmitted signals. This paper proposes contributions in three key areas. Firstly, we investigate the nonlinear effects of memoryless HPA, which is modeled using Saleh model, by deriving its Bit Error Rate expression (BER) in massive MIMO Orthogonal Frequency Division Multiplexing (OFDM) system. Secondly, we highlight the necessity of providing the accurate channel characteristics by estimating it using Compressive Sensing (CS) techniques. Moreover, we propose also a CS compensation algorithm based on Orthogonal Matching Pursuit (OMP) to mitigate the nonlinear distortion in the receiver. The proposed CS-based compensation technique has been compared to the Neural Network (NN) pre and post compensation technique and it has shown a good performance not only in terms of BER but also in terms of complexity.

Massive multi input multi output (MIMO) systems incorporate orthogonal frequency division multiplexing (OFDM) technology to render high data rate services for future wireless communication applications. The channel estimator (CE) employed by a reliable massive MIMO-OFDM system requires huge amount of overhead in the form of known and null data transmissions, hence limiting the system spectral efficiency (SE). Often, CE design is a tradeoff between SE and system reliability. In this paper, CE with three different overhead arrangements, namely time domain synchronous (TDS), comb type with cyclic prefix (CTCP), 2D grid type with cyclic prefix (GTCP) are investigated and a GTCP based CE is proposed which offers both high SE and improved system reliability. The proposed CE uses autocorrelation based denoising threshold for channel impulse response (CIR) estimation and does not require any knowledge of channel statistics (KCS). A 4 x 16 MIMO-OFDM system is simulated in a rayleigh fading c...

This paper proposes a new window based approach for the design of M-channel maximally decimated Near-Perfect Reconstruction (NPR) type transmultiplexer. Cosine modulation is used to design the synthesis and analysis sections of the transmult iplexer. The prototype filter is designed with high Side-Lobe-Fall-Off-Rate (SLFOR) co mb inational window functions. A gradient based optimization algorith m has been applied to minimize the interference parameters like Inter-Channel Interference (ICI) and Inter-Sy mbol Interference (ISI).The proposed method of design of transmultiplexers are showing the improvements in terms ICI and ISI.

(BER) degradation due to non-idealities in the transceiver (e.g. nonlinear distortions in the analog front-ends, digital clipping,...) is much more complicated in a multicarrier system than in a single-carrier system due to the large number of carriers and the huge number of possible transmitted symbols. This paper proposes a method for estimating the BER of such OFDM modulation schemes in a CPU time that is two orders of magnitude smaller than a Monte-Carlo method, as confirmed by simulations on a 5

Redundant multirate filter bank transceivers have recently been proposed for block-based transmission over channels whose characteristics are known at both the receiver and the transmitter. In this paper we propose a criterion for the design of such transceivers for applications in which the channel is not known at the transmitter. The design objective is the minimization of the average mean square error of the data estimates produced by a zero-forcing equalizer over a statistically modelled class of channels. Two solution methods are proposed, one of which appears to be amenable to modification for the solution of certain other robust performance problems. It is shown that the optimal transmitter provides substantially improved performance over a scheme based on multicarrier modulation.

Reliable communication in UnderWater (UW) environments is challenged by limited bandwidth, high temporal variability, and significant propagation delays. Orthogonal Frequency Division Multiplexing (OFDM) has emerged as a promising solution for UW communication; however, its performance heavily depends on dynamic subcarrier selection to adapt to fluctuating channel conditions. This paper presents MERMAID, a novel framework based on a Combinatorial Multi-Armed Bandit (CMAB) approach for adaptive subcarrier selection in Underwater Acoustic Networks (UANs). MERMAID dynamically activates subcarriers based on real-time Packet Delivery Ratio (PDR) feedback to maximize reliability while minimizing energy consumption. Unlike Deep Reinforcement Learning (DRL) techniques, which require extensive training and high computational overhead, MERMAID is specifically designed for resourceconstrained UW nodes, enabling fast convergence and lightweight operation. We implement MERMAID in the DESERT simulator and benchmark its performance against state-of-the-art DRL baselines. Simulation results show that MERMAID improves PDR by up to 21.15% and reduces energy consumption by up to 45.40%. These findings highlight MERMAID as a scalable, efficient, and high-performance solution for real-world Internet of Underwater Things (IoUT) applications. The framework aligns with the 6G vision by advancing intelligent and energy-efficient connectivity in harsh environments, highlighting its potential to extend communication paradigms to UW networks.

Orthogonal frequency division multiple access (OFDMA) systems exploit multiuser diversity and frequency selectivity to achieve high spectral efficiencies. However, they require considerable feedback for scheduling and rate adaptation, and are sensitive to feedback delays. We develop a comprehensive analysis of the OFDMA system throughput as a function of the feedback scheme, frequency-domain scheduler, and discrete rate adaptation rule in the presence of feedback delays. Previous allocation methods have been iterative nonlinear methods suitable for offline optimization. In the special high sub-channel SNR case, an iterative radical-jewel method has linear-time complexity in the number of users and N log N complexity in the number of sub-channels. We propose a non-iterative method that is made possible by our relaxation of strict user rate proportionality constraints. Compared to the radical-jewel method, the proposed method waives the restriction of high sub-channel SNR, has significantly lower complexity, and in simulation, yields higher user data rates. Adaptive where, the goal is to redistribute power such that the transmission time of a packet is minimized. While the first two variants decrease transceiver complexity and are simpler, the third is geared towards achieving the maximum throughput possible. We analyze the popular best-n and threshold-based feedback schemes.

We describe new concepts in broadband software define radio architectures optimized for very high bandwidth wireless communication protocols. This is important since a trend in wireless communication transceivers is the adoption of increasingly sophisticated radio link algorithms which maximize utility functions consisting of network capacity, data rate reliability, and throughput. Many prior efforts in software defined radio suffer from either a presumption that sufficiently high clock rates exist to employ traditional single instruction multiple data (SIMD) multi-processor architectures or that renaissance programmers are available to convert thousand page wireless protocol specifications into fine-grain data flow graphs at the operation level. The challenge for new generations of software defined radio is to maintain flexibility whiles simultaneously supporting computationally efficient broadband communication algorithms and ease of programming. Our system architecture is viable for wide varieties of communication protocols and physical data channels. We focus principally on OFDM transceiver styles due to their bandwidth scalability and their popularity in many next generation wireless air interfaces. Our SDR system jointly minimizes power, maximize algorithm flexibility, and to enable rapid software re-programming. We feel that these concepts are critical for the adoption of software defined radio in 21st century broadband wireless networks.

In this work, we propose a simple, yet flexible channel estimator for MIMO-OFDM systems. It works in the frequency domain, by interpolating among the estimates done in a small number of subcarriers. Our estimator can be easily used in either acquisition (preamble-based) or tracking (pilot-tones based) mode, and its structure remains the same for any type of training pattern in the two-dimensional time-frequency space. We also propose efficient preambles that allow identification of the MIMO channel with the lowest sacrifice in data rate. The training sequence we advocate consists of a set of OFDM symbols endowed with orthogonality properties, whose duration is much lower than the number of OFDM subcarriers, and which is robust against frequency misalignments. The feasibility of our approach is substantiated by computer simulation results obtained for IEEE 802.16 broadband fixed wireless channel models.

Orthogonal frequency division multiplexing (OFDM) is a multicarrier modulation scheme, which is widely used in many wireless communication systems due to its high data rate, high spectral efficiency, and immunity against multipath fading channels. However, an OFDM system suffers from high peak-toaverage power ratio (PAPR) of the transmitted signal. This paper focuses on the PAPR reduction of OFDM systems by using symbols interleaving and selective mapping (SLM) techniques. We compare the PAPR reduction performance of these methods. Simulation results indicate that the SLM technique is slightly better than the interleaving approach.

In this work, the problem of channel estimation in multicarrier communications with the Type-I even discrete cosine transform (DCT1e) is addressed. A novel scheme, based on using the DCT1e, both at the transmitter and the receiver, is introduced. The proposed approach does not require adding any redundancy or knowing the exact length of the channel's impulse response. By constructing a symmetric training sequence at the transmitter with enough leading and tail zeros, we show that an accurate estimation of the channel's impulse response can be attained. Simulations using the ITU-T pedestrian channel B illustrate the good behavior of the proposed scheme in terms of reconstruction signal to noise ratio.

In this work, the problem of channel estimation in multicarrier communications with the Type-I even discrete cosine transform (DCT1e) is addressed. A novel scheme, based on using the DCT1e, both at the transmitter and the receiver, is introduced. The proposed approach does not require adding any redundancy or knowing the exact length of the channel's impulse response. By constructing a symmetric training sequence at the transmitter with enough leading and tail zeros, we show that an accurate estimation of the channel's impulse response can be attained. Simulations using the ITU-T pedestrian channel B illustrate the good behavior of the proposed scheme in terms of reconstruction signal to noise ratio.

A simple method of improving orthogonal frequency division multiplexing (OFDM) receiver performance in an impulsive noise environment is to precede a conventional OFDM demodulator with blanking nonlinearity. This method is widely used in practice since it is efficient and very simple to implement. However, performance analysis of this scheme has not yet appeared. In this paper, we study performance of the OFDM receiver with blanking nonlinearity in the presence of impulsive noise. Closed form analytical expressions for the signal-to-noise ratio (SNR) at the output of blanking nonlinearity and the optimal blanking threshold that maximizes SNR are derived. Simulation results are provided that show good agreement with theory if the number of OFDM subcarriers is sufficiently large.

Wi-Fi backscatter communication offers a compelling solution for ultra-low-power and battery-free communication systems, especially within the Internet of Things (IoT) domain. By repurposing existing Wi-Fi infrastructure and ambient signals, backscatter systems achieve energy-efficient communication by reflecting signals rather than generating them. This review consolidates the current landscape of Wi-Fi backscatter technologies and highlights key areas of development such as feasibility on commercial hardware, antenna design, modulation techniques, synchronization, and safe Wi-Fi packet manipulation. Furthermore, the review identifies persistent research gaps and proposes future directions to bridge them, with emphasis on addressing four core challenges: hardware feasibility, antenna optimization, modulation reliability, and protocol-safe Wi-Fi packet analysis.

In this paper, the performances of a multicarrier modulation (COFDM) system in an urban mobile radio channel is analyzed using a computer-aided analysis tool called SPW. This multicarrier modulation system, with convolutional coding and interleaving, provides an extremely bandwidth efficient and multipath resistant transmission method. COFDM gives a remarkable performance in selective Rayleigh channels at a much higher bit rate than conventional systems.

The performances of two low-complexity HR adaptive filtering algorithms applied to the equalization of a typical transmission line channel are compared. The algorithms considered are the Simple Hyperstable Adaptive Recursive Filter (SHARF) and the stochastic gradient equation error algorithm. Gradient descent techniques are shown to be ill suited for transmission line channels.

In this paper a survey of power line communications has been presented. As power line distribution networks are available in almost each building that is mainly used for the supply of electrical power, it will be very interesting if such media could be used for the transmission of data. The demand of low cost telecommunication, broadband and access to internet services is increasing day by day and applied a driven force leading to further research in the field of power line communications. A number of organizations are working on power line communications and more advanced schemes are being proposed so that a new dimension could be added to the potential application of established wire line infrastructure.

The (MC-CDMA) is an advanced broadband wireless transmission technology combining (OFDM) and spread spectrum techniques. The MC-CDMA family can have several competitive properties, e.g., robustness against the frequency selective fading channel, flexibility in system design, low detection complexity, and lower peak-to-average power ratio. MCCDMA support multi-class traffic with different bit error rate .The study of BER performance ,SNR performance, Standard Deviation Of Phase Error performance , Peak Power Compression performance , Mutipath performance over different modulation techniques are obtained. The peak power compression ratio is the ratio of the peak power of the signal before clipping to the peak power of the clipped signal. In this peak power compression and standard deviation of phase error is computed. When the simulation take place the clipping signal effects the output power amplifier being over driven, therefore peak to RMS power of the signal is reduced and it allo...

In OFDM/OQAM systems, the presence of the intrinsic interference effect, caused by the lack of complex field orthogonality of the pulses employed, challenges the symbol detection task at the receiver. In this paper, the problem of equalization in such a system is studied, through the comparative analysis of three approaches to zero forcing equalization: (a) the classical receiver, which operates directly on the received signal at each subcarrier without any additional processing, (b) the dispersive receiver, forming sufficient statistics for the symbol decision, and (c) an alternative approach, which aims at completely eliminating intrinsic interference before deciding the symbols. The receivers are formulated and analyzed under the common assumptions for the OFDM/OQAM input/output model. The classical receiver is then shown to perform similarly with the other two for relatively short channels, while it outperforms them when the channel dispersion is large with respect to the number of subcarriers. Through these results, the sensitivity of the detection performance of alternative receivers to the validity of the input/output model is revealed and assessed.

Preamble-based channel estimation in filter bank-based multicarrier (FBMC) systems using offset quadrature amplitude modulation (OQAM) has been extensively studied in the last few years, due to the many advantages this modulation scheme can offer over cyclic prefix (CP)-based orthogonal frequency division multiplexing (OFDM) and in view of the interesting challenges posed on the channel estimator by the interference effect inherent in such an FBMC system. In particular, preambles of short duration and of both the block (full) and comb (sparse) types were designed so as to minimize the channel estimation mean squared error (MSE) subject to a given transmit energy. In the light of the important role that relay-based cooperative networks are expected to play in future wireless communication systems, it is of interest to consider FBMC/OQAM, and in particular questions associated to preamble-based channel estimation, in such a context as well. The goal of this paper is to address these problems and come up with optimal solutions that extend existing results in a single relay-based cooperative network. Both low and medium frequency selective channels are considered. In addition to optimal preamble and estimator design, the equalization/detection task is studied, shedding light to a relay-generated interference effect and proposing a simple way to come over it. The reported simulation results corroborate the analysis and reveal interesting behavior with respect to channel frequency selectivity and signal-to-noise ratio.

Recently, Coherent Optical Orthogonal Frequency Division Multiplexing (CO-OFDM) has been seen as a potential candidate for long haul optical transmission. It is due to OFDM technique that was proved as an effective solution for mitigating chromatic dispersion (CD) effects in optical communication systems. However, a very basic drawback of OFDM technique is large peak-to-average power ratio (PAPR) problem which requires large scale linear power amplifier and optical external modulator. The large PAPR leads to the increase of nonlinearity of optical fiber which depends on instantaneous signal power. So, the performance of CO-OFDM system is degraded. Several approaches were studied and applied in wireless communication. Among all techniques of Partial Transmit Sequence (PTS) is considered as the good method because of its distortionless characteristics. But the efficiency of this algorithm in long haul optical communication application is still an open issue. In this paper, we study PTS technique to reduce the influence of optics nonlinear effects. The Simulink simulation results are presented and discussed.

In this paper, we consider signal reception in multicarrier code-division multiple-access (MC-CDMA) systems. A blind adaptive algorithm is proposed to determine a weight vector which optimally combines the desired signal contributions from different carriers while suppressing noise and interference. No knowledge of the channel conditions (fading coefficients, signature sequences and timing of interferers, statistics of other noises, etc.) nor any training sequence is required. The performance is examined for Rayleigh fading channels. Results show that the proposed algorithm performs well and is robust to the near-far problem. Hence, the results show that MC-CDMA systems are attractive candidates for future CDMA systems.

This paper presents an efficient method for the design of M -channel oversampled warped cosine-modulated filter banks. The method consists in filter prototype design for synthesis filter bank using optimization procedure, which minimizes filter bank overall distortion transfer function. Optimization takes into account channel subsampling factors as well.