This work presents a novel, low-complexity hardware implementation of the Two-Choice Hard Thresholding Pursuit (TCHTP) algorithm for sparse channel estimation (CE) in the delay-Doppler (DD) domain, specifically designed for Orthogonal Time Frequency Space (OTFS) modulation. Unlike prior compressed sensing methods, the proposed approach does not require prior knowledge of channel sparsity or statistics, making it highly suitable for real-world, high-mobility scenarios. We formulate the CE problem in a sparse framework and develop a hardware-friendly variant of TCHTP that jointly estimates channel coefficients and their DD positions. To reduce complexity in the coefficient estimation stage involving the inverse operation, we explore and implement three matrix decomposition strategies—singular value decomposition (SVD), QR decomposition, and a novel hybrid QR+SVD approach—on a system-on-chip platform using hardware-software co-design. The proposed hybrid architecture achieves up to 70.6% memory savings, 42.4% reduction in DSP usage, and a$132\times $speedup over the conventional design, while maintaining BER performance. Additionally, it achieves 10% lower power consumption and delivers an$84.2\times $increase in end-to-end physical layer throughput.

In this paper, we design low-complexity hardware architectures for the basic modules of the two-dimensional (2D) modulation scheme, orthogonal time sequency multiplexing (OTSM). OTSM scheme works in the delay-sequence domain by using the basic modules inverse Walsh-Hadamard transform (IWHT) and Walsh-Hadamard transform (WHT) at the transmitter and receiver, respectively. We next compare the performance of the proposed architectures of the abovementioned basic modules with that of its counterpart modules of the another 2D modulation technique Zak based orthogonal time frequency space (OTFS). Note that Zak-OTFS operates in the delay-Doppler domain, requiring the primary modules as 2D inverse Zak (IZak) and Zak transforms at the transmitter and receiver, respectively. This comprehensive comparative analysis is conducted on the computational complexity, timing performance, and power consumption of both schemes, evaluated on the ZCU706 Zynq SoC board. The results indicate that OTSM outperforms the Zak-OTFS in terms of area, power consumption, and latency. Zak-OTFS requires more programmable logic (PL) resources, utilizing$\mathbf{2 8, 8 7 9}$LUTs and 26,124 FFs, while OTSM uses significantly fewer resources, with 5,440 LUTs and 6,216 FFs.

For high Doppler scenarios, intelligent reflecting surface (IRS)-aided orthogonal time frequency space (OTFS) systems exhibit enhanced performances in terms of bit-error rate (BER), achievable rate (AR), signal-to-noise ratio (SNR), etc. These performances can be achieved by optimally designing the IRS coefficients through solving proper optimization problems. Note that in the existing literature, for IRS-OTFS systems, the optimal reflection coefficients were designed by minimizing the BER, which may not achieve a highly spectral-efficient system. Therefore, in this work, we design reflection coefficients by developing an AR optimization framework. We propose a root-mean squared propagation (RMS-prop) approach to solve this optimization problem. On the other hand, OTFS system comprises a high dimension delay-Doppler matrix, which can increase the computational complexity of linear equalization techniques. Thus, in this work, we also design low-complexity linear-minimum-mean-squared-error (LMMSE) equalizers, for OTFS system (with and without IRS), which relies on the principle of Cholesky-based decomposition. Our simulation results demonstrate the efficacy of the proposed AR optimization framework and low-complexity equalizers in terms of AR, BER and computational complexity, compared to the existing state-of-the-art techniques.

In this paper, single-input single-output filter bank multicarrier (FBMC) waveform based on offset quadrature amplitude modulation (OQAM) is investigated in conjunction with intelligent reflecting surface (IRS). A frame structure for IRS assisted FBMC waveform is designed for channel frequency response (CFR) estimation, followed by IRS reflecting coefficients optimization. In particular, an ON/OFF channel estimation technique is proposed by inserting guard symbols between the adjacent training symbols. The guard symbols are utilized to mitigate the inter-symbol-interference between the adjacent training symbols, and to help in calculating the inherent intrinsic interference in FBMC waveform. We next investigate a random phase initialization based successive convex approximation technique to jointly optimize the IRS reflecting coefficients and sub-carriers transmit power allocation using both perfect and imperfect CFRs. Our simulation results demonstrate the accuracy of proposed CFR estimation and reflecting coefficient optimization schemes, and the effect of the guard symbols on their performances.

We derive closed form bit error rate (BER) expression for orthogonal time frequency space (OTFS) zero-forcing (ZF) receiver with perfect and imperfect receive channel information. Depending on the delay-Doppler locations of the propagation paths of the OTFS channel H, the expression$\mathrm {H}^{H}\mathrm {H}$is shown to have either distinct or repetitive eigenvalues. When$\mathrm {H}^{H}\mathrm {H}$has two or less distinct eigenvalues and the remaining ones are repetitive, we derive the probability distribution function (pdf) of the signal-to-noise-plus-interference-ratio (SINR) of the ZF receiver. A closed form BER expression is then derived by averaging the conditional BER over the SINR pdf. When$\mathrm {H}^{H}\mathrm {H}$has$n$distinct eigenvalues, we use numerical integration to derive a generalized expression for the SINR pdf. We show that this pdf can be tightly approximated by the Gamma pdf, and then use it to derive the BER expression. The derived OTFS ZF BER expression therefore, unlike the existing ones in the literature, does not require averaging over multiple channel realizations. We show, for different modulation schemes and OTFS system parameters, that the BER calculated using the derived expressions closely matches the one calculated numerically.

We propose a superimposed pilot (SP)-based channel estimation and data detection framework for orthogonal time-frequency space (OTFS) systems, which superimposes low-powered pilots on to data symbols in the delay-Doppler domain. We propose two channel estimation and data detection designs for SP-OTFS systems which, unlike the existing OTFS designs, do not designate any slots for pilots, and consequently have higher spectral efficiency (SE). The first SP design estimates channel by treating data as interference, which degrades its performance at high signal to noise ratio. The second SP design alleviates this problem by iterating between channel estimation and data detection. Both these designs detect data using message passing algorithm which exploits OTFS channel sparsity, and consequently has low computational complexity. We also derive a lower bound on the signal-to-interference-plus-noise ratio of the proposed designs and maximize it by optimally allocating power between data and pilot symbols. We numerically validate the derived analytical results, and show that the proposed designs have superior SE than the existing OTFS channel estimation and data detection designs.

This paper investigates uplink rate performance of filter bank multicarrier (FBMC)-offset quadrature amplitude modulation (OQAM) based multi-user (MU) multicell massive multiple-input multiple-output (MIMO) systems. Contrary to existing works in the FBMC literature, channel between users and the base station (BS) within a cell is modelled to be Ricean fading with a deterministic fast fading component and a random Rayleigh distributed component. Closed-form expressions for the ergodic achievable uplink sum rate and corresponding approximation are derived for the maximum ratio combining (MRC) at the BS in the presence of imperfect channel state information (CSI). This is achieved by considering the effect of pilot contamination, and the statistical characteristics of the intrinsic interference in FBMC systems. Uplink power scaling laws with imperfect CSI at the BS are investigated. Analytical results are also developed for analysing the effect of the Ricean-K factor on the achievable uplink sum rate. Numerical examples are presented to demonstrate the tightness between the analysis and simulations, and to compare the performance of FBMC-OQAM and traditional OFDM-based MU multi-cell massive MIMO systems.

This paper analyses the performance of filter bank multicarrier (FBMC) signaling in conjunction with offset quadrature amplitude modulation (OQAM) in multi-user (MU) massive multiple-input multiple-output (MIMO) systems. Initially, closed form expressions are derived for tight lower bounds corresponding to the achievable uplink sum-rates for FBMC-based single-cell MU massive MIMO systems relying on maximum ratio combining (MRC), zero forcing (ZF) and minimum mean square error (MMSE) receiver processing with/without perfect channel state information (CSI) at the base station (BS). This is achieved by exploiting the statistical properties of the intrinsic interference that is characteristic of FBMC systems. Analytical results are also developed for power scaling in the uplink of MU massive MIMO-FBMC systems. The above analysis of the achievable sum-rates and corresponding power scaling laws is subsequently extended to multi-cell scenarios considering both perfect as well as imperfect CSI, and the effect of pilot contamination. The delay-spread-induced performance erosion imposed on the linear processing aided BS receiver is numerically quantified by simulations. Numerical results are presented to demonstrate the close match between our analysis and simulations, and to illustrate and compare the performance of FBMC and traditional orthogonal frequency division multiplexing (OFDM)-based MU massive MIMO systems.

This paper analyses peak to average power ratio (PAPR) of superimposed training sequence (STS) based multiple input multiple output filter bank multi carrier (MIMO-FBMC) offset quadrature amplitude modulation (OQAM) systems using complementary cumulative distribution function (CCDF). The results of this method are compared with complex training sequence decomposition (CTSD) based MIMO-FBMC OQAM systems.

This paper investigates the zero forcing (ZF) based vertical Bell laboratories layered space-time (V-BLAST) detection in multiple input multiple output (MIMO) filter bank multicarrier (FBMC) systems based on the offset quadrature amplitude modulation (OQAM). Initially, a QR decomposition based convectional ZF-successive interference cancellation (C-ZF-SIC) technique is examined for the detection in MIMO-FBMC-OQAM systems. In order to tackle intense error propagation in the C-ZF-SIC scheme due to the intrinsic interference in FBMC systems, a neighbourhood detection based ZF-SIC (ND-ZF-SIC) technique is proposed that exploits the fact that each symbol in the FBMC-OQAM system interferes only with the symbols within a small neighbourhood. Further, the ND-ZF-SIC scheme based on the sorted QR decomposition (ND-ZF-SQRD) is also investigated for the detection in MIMO-FBMC-OQAM systems. Simulation results demonstrate that the proposed schemes significantly outperform the conventional scheme, and attain a performance similar to that of MIMO-OFDM systems.

In this paper, we study energy transmission for decentralized detection in wireless powered sensor networks (WPSN) in which the sensor nodes are powered by harvesting the radio frequency signals transmitted from dedicated energy access points (E-AP). We present a joint design of the transmit covariance matrices at E-APs and sensor precoders to minimize the probability of error. To this end, we maximize the error exponents by employing Dinkelbach's method and semidefinite relaxation. We present an iterative algorithm to solve the relaxed problem and prove that the relaxation is tight. Simulation results demonstrate that the proposed design results in a superior detection performance in comparison to the conventional techniques.

In this study, the design of a superimposed training (ST) for an interference‐limited spatially correlated multiple‐input–multiple‐output (MIMO) system is addressed and a closed‐form solution for designing the training signal is proposed in a sub‐optimal way. Earlier papers have considered noise limited MIMO systems. The authors also propose random/orthogonal variable spread factor (OVSF) codes as a choice for the ST signal. The mean‐squared error of the channel estimate and symbol error rate performances are obtained through simulation. Considering the power allocation issue between the data and training symbols, a sub‐optimal average training power that maximises the lower bound on the effective signal‐to‐interference ratio is also proposed. Simulation results show that the bit error rate performance of the ST is indistinguishable from the OVSF/random ST sequence.