Fluid antenna (FA) is an emerging technology in recent years to switch physical locations of antennas in a predetermined small space. This paper proposes a reconfigurable intelligent surfaces (RIS)-cooperative framework with FA-assisted non-orthogonal multiple access (NOMA) system, namely FA-RIS-NOMA. Targeting multi-interference scenarios in urban environments, the considered system incorporates a base station (BS) equipped with a conventional antenna and users each equipped with an FA. Additionally, the RIS is utilized to forward signals between BS and users blocked by obstacles. The non-line-of-sight multipath fading characteristics of the RIS-assisted link are modeled as a Nakagami-mchannel. To overcome the multiuser interference and improve the system performance, we develop the NOMA technique for resource allocation. Meanwhile, to reduce the signal processing complexity at the receiver, a group optimization greedy detection method is proposed. To evaluate the system’s reliability, the outage probability for each user is analyzed by using the copula function. This method enables the derivation of the cumulative distribution and probability density functions for the equivalent user-side channel, from which closed-form outage probability expressions are obtained. Numerical results demonstrate that the proposed framework achieves signal-to-noise ratio gains of approximately 9 dB and 8 dB over fixed-antenna and relay-assisted systems, respectively. Furthermore, the proposed detection method reduces computational complexity by over 75% with less than 0.5 dB performance degradation.

Affine frequency division multiplexing (AFDM) has been considered as a promising waveform to enable high-reliable connectivity in the internet of vehicles. However, accurate channel estimation is critical and challenging to achieve the expected performance of the AFDM systems in doubly-dispersive channels. In this paper, we propose a sparse Bayesian learning (SBL) framework for AFDM systems and develop a dynamic grid update strategy with two off-grid channel estimation methods, i.e., grid-refinement SBL (GR-SBL) and grid-evolution SBL (GE-SBL) estimators. Specifically, the GR-SBL employs a localized grid refinement method and dynamically updates grid for a high-precision estimation. The GE-SBL estimator approximates the off-grid components via first-order linear approximation and enables gradual grid evolution for estimation accuracy enhancement. Furthermore, we develop a distributed computing scheme to decompose the large-dimensional channel estimation model into multiple manageable small-dimensional sub-models for complexity reduction of GR-SBL and GE-SBL, denoted as distributed GR-SBL (D-GR-SBL) and distributed GE-SBL (D-GE-SBL) estimators, which also support parallel processing to reduce the computational latency. Finally, simulation results demonstrate that the proposed channel estimators outperform existing competitive schemes. The GR-SBL estimator achieves high-precision estimation with fine step sizes at the cost of high complexity, while the GE-SBL estimator provides a better trade-off between performance and complexity. The proposed D-GR-SBL and D-GE-SBL estimators effectively reduce complexity and maintain comparable performance to GR-SBL and GE-SBL estimators, respectively.

Spectral efficiency (SE) and energy efficiency (EE) are two major challenges faced by the sixth-generation wireless communication systems. In this paper, we propose a reconfigurable intelligent surfaces-assisted simultaneous wireless information and power transfer scheme based on fluid antenna port grouping index modulation (RIS-FA-PGIM). The flexible port switching capability of FA overcomes the spatial limitations of traditional antennas, significantly improving the SE. Further-more, in order to improve the SE and EE of the system, this paper jointly optimizes the beamforming matrix at the base station and RIS. Due to the coupling relationship between variables, the optimization problem is non-convex and difficult to solve. In order to solve this problem, an alternating optimization algorithm is proposed, which gradually approaches the global optimal solution through an iterative optimization process. Simulation results show that the system not only achieves outstanding SE performance but also realizes low energy consumption, which verifies the effectiveness and superiority of the scheme.

The integration of multicarrier modulation and multiple-input-multiple-output (MIMO) is critical for reliable transmission of wireless signals in complex environments, which significantly improve spectrum efficiency. Existing studies have shown that popular orthogonal time frequency space (OTFS) and affine frequency division multiplexing (AFDM) offer significant advantages over orthogonal frequency division multiplexing (OFDM) in uncoded doubly selective channels. However, it remains uncertain whether these benefits extend to coded systems. Meanwhile, the information-theoretic limit analysis of coded MIMO multicarrier systems and the corresponding low-complexity receiver design remain unclear. To overcome these challenges, this paper proposes a multi-slot cross-domain memory approximate message passing (MS-CD-MAMP) receiver as well as develops its information-theoretic (i.e., achievable rate) limit and optimal coding principle for MIMO-multicarrier modulation (e.g., OFDM, OTFS, and AFDM) systems. The proposed MS-CD-MAMP receiver can exploit not only the time domain channel sparsity for low complexity but also the corresponding symbol domain constellation constraints for performance enhancement. Meanwhile, limited by the high-dimensional complex state evolution (SE), a simplified single-input single-output variational SE is proposed to derive the achievable rate of MS-CD-MAMP and the optimal coding principle with the goal of maximizing the achievable rate. Numerical results show that coded MIMO-OFDM/OTFS/AFDM with MS-CD-MAMP achieve the same maximum achievable rate in doubly selective channels, whose finite-length performance with practical optimized low-density parity-check (LDPC) codes is only$0.5\sim 1.8$dB away from the associated theoretical limit, and has$0.8\sim 4.4$dB gain over the well-designed point-to-point LDPC codes.

The recently proposed affine frequency division multiplexing (AFDM) modulation has been considered as a promising technology for narrowband doubly-dispersive channels. However, the time-scaling effects, i.e., pulse widening and pulse shortening phenomena, in extreme wideband doubly-dispersive channels have not been considered in the literatures. In this paper, we investigate such wideband transmission and develop an efficient transmission structure with chirp-periodic prefix (CPP) and chirp-periodic suffix (CPS) for AFDM system. We derive the input-output relationship of AFDM system under time-scaled wideband doubly-dispersive channels and demonstrate the sparsity in discrete affine Fourier (DAF) domain equivalent channels. We further optimize the AFDM chirp parameters to accommodate the time-scaling characteristics in wideband doubly-dispersive channels and verify the superiority of the derived chirp parameters by pairwise error probability (PEP) analysis. We also develop an efficient cross domain distributed orthogonal approximate message passing (CD-D-OAMP) algorithm for AFDM symbol detection and analyze its corresponding state evolution. By analyzing the detection complexity of CD-D-OAMP detector and evaluating the error performance of AFDM systems based on simulations, we demonstrate that the AFDM system with our optimized chirp parameters outperforms the existing competitive modulation schemes in time-scaled wideband doubly-dispersive channels. Moreover, our proposed CD-D-OAMP detector can achieve the desirable trade-off between the complexity and performance, while supporting parallel computing to significantly reduce the computational latency.

Affine frequency division multiplexing (AFDM) exhibits strong robustness against time and frequency dispersion in doubly dispersive channels (DDCs), enabling reliable communication under high mobilities. However, in the multi-user uplink scenario, inter-user channel delay and Doppler differences in the discrete affine Fourier transform (DAFT) domain manifest as inevitable multi-user interference (MUI). To address this issue, building upon the DAFT and AFDM, we propose a novel uplink multiple access scheme termed as DAFT-spread affine frequency division multiple access (DAFT-s-AFDMA). In our proposed scheme, DAFT spreading is performed by each user to multiplex the transmitted symbols over the DAFT domain, which includes a pre-chirp parameter that can be flexibly adjusted to reduce the peak-to-average power ratio (PAPR) of the AFDM system. Accordingly, we derive new guidelines for setting the DAFT parameters and the asymptotically tight upper bounds on the average bit error rate, revealing the insights of PAPR reduction. Furthermore, a low-complexity cross-domain expectation propagation (CD-EP) detector is proposed, capitalizing on the sparsity of DAFT domain effective channel matrix and the corresponding symbol domain constellation constraints to enhance the error performance. Simulation results show that the proposed CD-EP detector outperforms both conventional Gaussian message passing (GMP) and minimum mean square error (MMSE) detectors with a much lower complexity, and also verify the superiority of DAFT-s-AFDMA to plain AFDMA across various scenarios of high-mobility DDCs.

Extremely large-scale reconfigurable intelligent surface (XL-RIS) can effectively overcome severe fading and provide higher communication performance. However, current research on XL-RIS overlooks the discrete phase-shift characteristics of RIS in practical systems, which will result in significant performance degradation. In this paper, we investigate near-field communication schemes assisted by XL-RIS with discrete phase shifts. Specifically, we propose a hierarchical beam training method to obtain the user channel state information (CSI), and develop the jointly optimized codebook construction (JOCC) method and separately optimized codebook construction (SOCC) method for base station (BS) precoding and XL-RIS phase shifts, respectively. With JOCC, the most superior beam training performance can be obtained. With SOCC, higher performance than the single-antenna BS codebook can be obtained at a similar complexity. Further, we propose a flexible multiuser interference management (IM) method that is simple to solve. The IM method uses adaptive gain matrix approximation to take into account user fairness and can be solved in closed-form iterations. In addition, we extend the proposed method to a hybrid precoding design. Simulation results demonstrate that the proposed multi-resolution codebook construction method can obtain more accurate beam patterns and user CSI, and the proposed IM method obtains superior performance over the benchmark methods.

Stacked intelligent metasurfaces (SIM) provide a cost-effective and scalable solution for large-scale antenna communications. However, efficient channel state information acquisition and phase shift optimization remain critical challenges. In this paper, we develop a unified framework of low-complexity algorithms for SIM-assisted communication systems to address these issues. Specifically, we propose a generalized two-step codebook construction (TSCC) method that lever-ages two-dimensional angular-domain decoupling to transform planar array beamformer design into two independent one-dimensional linear array beamformer design problems, efficiently solved via the Gerchberg–Saxton algorithm and our proposed majorization–minimization-based proximal-distance (PDMM) algorithm. We further develop a two-stage coded-sliding beam training (TSCSBT) method for low-overhead and high-accuracy beam training, where error-correcting codes are embedded in the first-stage training to enhance robustness against noise, and sliding sampling is subsequently performed around the matched angular samples to improve angular resolution. The proposed framework is further extended to multi-path user channels. Finally, a variable decoupling-based block successive upper bound minimization (VD-BSUM) algorithm is proposed to directly solve the QoS-constrained sum-rate maximization problem through closed-form iterative updates with substantially reduced computational complexity. Simulation results demonstrate the effectiveness of the proposed methods in achieving precise beam pattern realization, improved beam training accuracy and angular resolution, and enhanced sum-rate performance.

Affine frequency division multiplexing (AFDM)-based orthogonal multiple access (OMA) suffers from rank deficiency of the effective channel matrix, which degrades the performance of minimum mean square error (MMSE) detection. To address this issue, in this paper, we propose a partially-overlapping AFDM-OMA scheme that inserts a cyclic prefix (CP) in the discrete affine Fourier (DAF) domain for each user and assigns different inverse discrete affine Fourier transform (IDAFT) parameters to different users. With CP insertion and a user-specific parameter strategy, the effective channel matrix is guaranteed to be full-rank. We theoretically analyze the relation-ship between the rank of the channel matrix and the lower bound of the bit error rate (BER), and demonstrate the superiority of the proposed scheme compared to the benchmarks. Simulation results show that the proposed scheme achieves improved BER performance and validate the effectiveness of assigning user-specific IDAFT parameters.

The recently proposed multi-chirp waveform, affine frequency division multiplexing (AFDM), is considered as a potential candidate for integrated sensing and communication (ISAC). However, acquiring accurate target sensing parameter information becomes challenging due to fractional delay and Doppler shift occurrence, as well as effects introduced by the coexistence of near-field (NF) and far-field (FF) targets associated with large-scale antenna systems. In this paper, we propose a novel angle-delay-Doppler estimation scheme for AFDM-ISAC system in mixed NF and FF scenarios. Specifically, we model the received ISAC signals as a third-order tensor that admits a low-rank CANDECOMP/PARAFAC (CP) format. By employing the Vandermonde nature of the factor matrix and the spatial smoothing technique, we develop a structured CP decomposition method that guarantees the condition for uniqueness. We further propose a low-complexity estimation scheme to acquire target sensing parameters with fractional values, including angle of arrival/departure (AoA/AoD), delay and Doppler shift accurately. We also derive the Cramér-Rao Lower Bound (CRLB) as a benchmark and analyze the complexity of our proposed scheme. Finally, simulation results are provided to demonstrate the effectiveness and superiority of our proposed scheme.

Affine frequency division multiplexing (AFDM) is a novel modulation technique based on chirp signals that has been recently proposed as an effective solution for highly reliable communications in high-mobility scenarios. In this paper, we focus on the design of robust index modulation (IM) schemes under the multiple-antenna AFDM transmission framework. To this end, the cyclic delay diversity (CDD) technique is employed to harvest the transmit diversity gain. As a result, we propose two novel AFDM-IM schemes with transmit diversity, termed as CDD-AFDM-IM-I and CDD-AFDM-IM-II. We analyze the full diversity conditions and parameter settings of the proposed CDD-AFDM-IM schemes for both integer and fractional Doppler cases over linear time-varying (LTV) channels. Moreover, we prove that IM enables AFDM to have stronger diversity protection when the full diversity condition is not satisfied. Asymptotically tight upper bounds on the average bit error rates (BERs) of the proposed schemes with maximum-likelihood (ML) detection are derived in closed-form. Furthermore, we propose a low-complexity double-layer message passing (DLMP) algorithm for practical large-dimensional signal detection in the proposed CDD-AFDM-IM systems. Comparison with existing detections shows that the proposed DLMP algorithm achieves a better tradeoff between the BER performance and the computational complexity. Finally, BER simulation results confirm that our proposed CDD-AFDM-IM schemes with both the ML and DLMP detections outperform the benchmark schemes over the LTV channels.

Orthogonal time frequency space (OTFS) modulation and massive multi-input multi-output (MIMO) are promising technologies for next generation wireless communication systems for their abilities to counteract the issue of high mobility with large Doppler spread and mitigate the channel path attenuation, respectively. The natural integration of massive MIMO with OTFS in millimeter-wave systems can improve communication data rate and enhance the spectral efficiency. However, when transmitting wideband signals with large-scale arrays, the beam squint effect may occur, causing discrepancies in beam directions across subcarriers in multi-carrier systems. Moreover, the high-mobility wideband millimeter wave communications can induce the Doppler squint effect, leading to different Doppler shifts among the subcarriers. Both beam squint effect and Doppler squint effect (denoted as doubly squint effect) can degrade communication performance significantly. In this paper, we present an efficient channel estimation and hybrid precoding scheme to address the doubly squint effect in massive MIMO-OTFS systems. We first characterize the wideband channel model and the input-output relationship for massive MIMO-OTFS transmission considering doubly squint effect. We then mathematically derive the impact of channel parameters on chirp pilots under the doubly squint effect. Additionally, we develop a peak-index-based channel estimation scheme. By leveraging the results from channel estimation, we propose a hybrid precoding method to mitigate the doubly squint effect in downlink transmission scenarios. Finally, simulation results validate the effectiveness of our proposed scheme and show its superiority over the existing schemes.

This paper presents generalized Arlery-Tan-Rabaste-Levenshtein lower bounds on the maximum aperiodic ambiguity function (AF) magnitude of unimodular sequences under certain delay-Doppler low ambiguity zones (LAZ). Our core idea is to explore the upper and lower bounds on the Frobenius norm of the weighted auto- and cross-AF matrices by introducing two weight vectors associated with the delay and Doppler shifts, respectively. As a second major contribution, we demonstrate that our derived lower bounds are asymptotically achievable with selected Chu sequence sets by analyzing their maximum auto- and cross-AF magnitudes within certain LAZ.

Affine frequency division multiplexing (AFDM) and orthogonal AFDM access (O-AFDMA) are promising techniques based on chirp signals, which are able to suppress the performance deterioration caused by Doppler shifts in high-mobility scenarios. However, the high peak-to-average power ratio (PAPR) in AFDM or O-AFDMA is still a crucial problem, which severely limits their practical applications. In this paper, we propose a discrete affine Fourier transform (DAFT)-spread AFDMA scheme based on the properties of the AFDM systems, named DAFT-s-AFDMA to significantly reduce the PAPR by resorting to the DAFT. We formulate the transmitted time-domain signals of the proposed DAFT-s-AFDMA schemes with localized and interleaved chirp subcarrier allocation strategies. Accordingly, we derive the guidelines for setting the DAFT parameters, revealing the insights of PAPR reduction. Finally, simulation results of PAPR comparison in terms of the complementary cumulative distribution function (CCDF) show that the proposed DAFT-s-AFDMA schemes with localized and interleaved strategies can both attain better PAPR performances than the conventional O-AFDMA scheme.

Affine frequency division multiplexing (AFDM) is a new multicarrier technique based on chirp signals tailored for high-mobility communications, which can achieve full diversity. In this paper, we propose an index modulation (IM) scheme based on the framework of AFDM systems, named AFDM-IM. In the proposed AFDM-IM scheme, the information bits are carried by the activation state of the subsymbols in the discrete affine Fourier (DAF) domain in addition to the conventional constellation symbols. To efficiently perform IM, we divide the subsymbols in the DAF domain into several groups and consider both the localized and distributed strategies. An asymptotically tight upper bound on the average bit error rate (BER) of the maximum-likelihood detection in the existence of channel estimation errors is derived in closed-form. Computer simulations are carried out to evaluate the performance of the proposed AFDM-IM scheme, whose results corroborate its superiority over the benchmark schemes in the linear time-varying channels. We also evaluate the BER performance of the index and modulated bits for the AFDM-IM scheme with and without satisfying the full diversity condition of AFDM. The results show that the index bits have a stronger diversity protection than the modulated bits even when the full diversity condition of AFDM is not satisfied.

Integrated sensing and communication (ISAC) has become a promising technology for future communication system. In this paper, we consider a millimeter wave system over high mobility scenario, and propose a novel simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) aided ISAC scheme. To improve the communication service of the in-vehicle user equipment (UE) and simultaneously track and sense the vehicle with the help of nearby roadside units (RSUs), a STAR-RIS is equipped on the outside surface of the vehicle. Firstly, an efficient transmission structure for the ISAC scheme is developed, where a number of training sequences with orthogonal precoders and combiners are respectively utilized at BS and RSUs for channel parameter extraction. Then, the near-field static channel model between the STAR-RIS and in-vehicle UE as well as the far-field time-frequency selective BS-RIS-RSUs channel model are characterized. By utilizing the multidimensional orthogonal matching pursuit (MOMP) algorithm, the cascaded channel parameters (i.e., the delays, the Doppler frequency shifts, the angles of arrivals, and the angles of departure of the scattering paths) of the BS-RIS-RSUs links can be obtained at the RSUs. Thus, the vehicle localization and its velocity measurement can be acquired by jointly utilizing these extracted cascaded channel parameters of all RSUs. Note that the MOMP algorithm can be further utilized to extract the channel parameters of the BS-RIS-UE link for communication service. With the help of sensing results, the reflection and refraction phase shifts of the STAR-RIS are delicately designed, which can significantly improve the received signal strength for both the RSUs and the in-vehicle UE, and can finally enhance the sensing and communication performance. Moreover, the trade-off design for sensing and communication is proposed by optimizing the energy splitting factors of the STAR-RIS. Finally, simulation results are provided to validate the feasibility and effectiveness of our proposed STAR-RIS aided ISAC scheme.

Orbital angular momentum (OAM) is a mode division multiplexing (MDM) technique enabling simpler implementation and higher capacity than conventional multiple-input multiple-output (MIMO) over line-of-sight (LoS) channels. This paper studies the joint design of protograph low-density parity-check (PLDPC) codes and shaping index modulation (IM) in OAM systems. To begin with, we analyze the distribution of extrinsic log-likelihood-ratios (LLRs) for coded bits output from channel detector, and then propose a customized Box-Cox transformation (CBCT) to make the distribution achieve symmetry and Gaussian features. We also devise a CBCT-based protograph extrinsic information transfer (CBCT-PEXIT) algorithm to predict the convergence performance of PLDPC-coded OAM systems. Furthermore, with the aid of such an algorithm, we construct two new types of improved PLDPC codes tailored for OAM systems, including unpunctured codes and rate-compatible punctured codes. In addition, we present a two-step design method, which seamlessly combines the shaping technique and index rule into a novel modulation scheme, calledshaping index. Both theoretical analyses and simulation results demonstrate that the proposed PLDPC-coded OAM systems with shaping index significantly outperform state-of-the-art counterparts.

Integrated sensing and communication (ISAC) has become a promising technology for future communication system. In this paper, we consider a millimeter wave system over high mobility scenario, and propose a novel simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) aided ISAC scheme. To improve the communication service of the in-vehicle user and simultaneously track and sense the vehicle with the help of nearby roadside units (RSUs), a STAR-RIS is equipped on the outside surface of the vehicle to transmit and reflect the signal from the base station (BS). Firstly, an efficient transmission structure for the ISAC scheme is designed. Then, the time-frequency selective BS-RIS-RSUs channel model are characterized. Based on the estimated cascaded channel parameters (i.e., the delays, the Doppler frequency shifts, the angles of arrivals, and the angles of departure of the scattering paths) of the BS-RIS-RSUs links, the vehicle localization and its velocity can be acquired. With the help of sensing results, the reflection and refraction phase shifts of the STAR-RIS are designed for performance enhancememt. Moreover, the trade-off design for sensing and communication is proposed by optimizing the energy splitting factors of the STAR-RIS. Finally, simulation results are provided to validate the feasibility and effectiveness of our proposed STAR-RIS aided ISAC scheme.

Energy efficiency (EE) problem has become an important and major issue in satellite communications. In this paper, we study the beamforming design strategy to maximize the EE of rate-splitting multiple access (RSMA) for the multibeam satellite communications by considering imperfect channel state information at the transmitter (CSIT). We propose an expectation-based robust beamforming algorithm against the imperfect CSIT scenario. By combining the successive convex approximation (SCA) with the penalty function transformation, the nonconvex EE maximization problem can be solved in an iterative manner. The simulation results demonstrate the effectiveness and superiority of RSMA over traditional space-division multiple access (SDMA). Moreover, our proposed beamforming algorithm can achieve better EE performance than the conventional beamforming algorithm.

As a promising technique for high-mobility wireless communications, orthogonal time frequency space (OTFS) has been proven to enjoy excellent advantages with respect to traditional orthogonal frequency division multiplexing (OFDM). Although multiple studies have considered index modulation (IM) based OTFS (IM-OTFS) schemes to further improve system performance, a challenging and open problem is the development of effective IM schemes and efficient receivers for practical OTFS systems that must operate in the presence of channel delays and Doppler shifts. In this paper, we propose two novel block-wise IM schemes for OTFS systems, named delay-IM with OTFS (DeIM-OTFS) and Doppler-IM with OTFS (DoIM-OTFS), where a block of delay/Doppler resource bins are activated simultaneously. Based on a maximum likelihood (ML) detector, we analyze upper bounds on the average bit error rates for the proposed DeIM-OTFS and DoIM-OTFS schemes, and verify their performance advantages over existing IM-OTFS systems. We also develop a multi-layer joint symbol and activation pattern detection (MLJSAPD) algorithm and a customized message passing detection (CMPD) algorithm for our proposed DeIM-OTFS and DoIM-OTFS systems with low complexity. Simulation results demonstrate that our proposed MLJSAPD and CMPD algorithms can achieve desired performance with robustness to the imperfect channel state information (CSI).

This article investigates a distant proactive eavesdropping system in cooperative cognitive radio (CR) networks. Specifically, an amplify-and-forward (AF) full-duplex (FD) secondary transmitter assists to relay the received signal from suspicious users to legitimate monitor for wireless information surveillance. In return, the secondary transmitter is granted to share the spectrum belonging to the suspicious users for its own information transmission. To improve the eavesdropping, the transmitted secondary user’s (SU) signal can also be used as a jamming signal to moderate the data rate of the suspicious link. We consider two cases, i.e., nonnegligible processing delay (NNPD) and negligible processing delay (NPD) at the secondary transmitter. Our target is to maximize network energy efficiency (NEE) via jointly optimizing the AF relay matrix and precoding vector at the secondary transmitter, as well as the receiver combining vector at the monitor, subject to the maximum power constraint at the secondary transmitter and minimum data rate requirement of the SU. We also guarantee that the achievable data rate of the eavesdropping link should be no less than that of the suspicious link for efficient surveillance. Due to the nonconvexity of the formulated NEE maximization problem, we develop an efficient path-following algorithm and a robust alternating optimization (AO) method as solutions under perfect and imperfect channel state information (CSI) conditions, respectively. We also analyze the convergence and computational complexity of the proposed schemes. Numerical results are provided to validate the effectiveness of our proposed schemes.

For high mobility communication scenario, the recently emerged orthogonal time frequency space (OTFS) modulation introduces a new delay-Doppler domain signal space, and can provide better communication performance than traditional orthogonal frequency division multiplexing system. This article focuses on the joint channel estimation and data detection (JCEDD) for hybrid reconfigurable intelligent surface (HRIS) aided millimeter wave (mmWave) OTFS systems. Firstly, a new transmission structure is designed. Within the pilot durations of the designed structure, partial HRIS elements are alternatively activated. The time domain channel model is then exhibited. Secondly, the received signal model for both the HRIS over time domain and the base station over delay-Doppler domain are studied. Thirdly, by utilizing channel parameters acquired at the HRIS, an HRIS beamforming design strategy is proposed. For the OTFS transmission, we propose a JCEDD scheme over delay-Doppler domain. In this scheme, message passing (MP) algorithm is designed to simultaneously obtain the equivalent channel gain and the data symbols. On the other hand, the channel parameters, i.e., the Doppler shift, the channel sparsity, and the channel variance, are updated through expectation-maximization (EM) algorithm. By iteratively executing the MP and EM algorithm, both the channel and the unknown data symbols can be accurately acquired. Finally, simulation results are provided to validate the effectiveness of our proposed JCEDD scheme.

We investigate a coded uplink non-orthogonal multiple access (NOMA) configuration in which groups of co-channel users are modulated in accordance with orthogonal time frequency space (OTFS). We take advantage of OTFS characteristics to achieve NOMA spectrum sharing in the delay-Doppler domain between stationary and mobile users. We develop an efficient iterative turbo receiver based on the principle of successive interference cancellation (SIC) to overcome the co-channel interference (CCI). We propose two turbo detector algorithms: orthogonal approximate message passing with linear minimum mean squared error (OAMP-LMMSE) and Gaussian approximate message passing with expectation propagation (GAMP-EP). The interactive OAMP-LMMSE detector and GAMP-EP detector are respectively assigned for the reception of the stationary and mobile users. We analyze the convergence performance of our proposed iterative SIC turbo receiver by utilizing a customized extrinsic information transfer (EXIT) chart and simplify the corresponding detector algorithms to further reduce receiver complexity. Our proposed iterative SIC turbo receiver demonstrates performance improvement over existing receivers and robustness against imperfect SIC process and channel state information uncertainty.

The recent emergence of orthogonal time frequency space (OTFS) modulation as a novel PHY-layer mechanism is more suitable in high-mobility wireless communication scenarios than traditional orthogonal frequency division multiplexing (OFDM). Although multiple studies have analyzed OTFS performance using theoretical and ideal baseband pulseshapes, a challenging and open problem is the development of effective receivers for practical OTFS systems that must rely on non-ideal pulseshapes for transmission. This work focuses on the design of practical receivers for OTFS. We consider a fractionally spaced sampling (FSS) receiver in which the sampling rate is an integer multiple of the symbol rate. For rectangular pulses used in OTFS transmission, we derive a general channel input-output relationship of OTFS in delay-Doppler domain without the common reliance on impractical assumptions such as ideal bi-orthogonal pulses and on-the-grid delay/Doppler shifts. We propose two equalization algorithms: iterative combining message passing (ICMP) and turbo message passing (TMP) for symbol detection by exploiting delay-Doppler channel sparsity and the channel diversity gain via FSS. We analyze the convergence performance of TMP receiver and propose simplified message passing (MP) receivers to further reduce complexity. Our FSS receivers demonstrate stronger performance than traditional receivers and robustness to the imperfect channel state information knowledge.

In this work, we consider a cognitive radio system, where the primary user (PU) owns the spectrum but has scarce energy while the secondary users (SUs) have adequate energy but lack of spectrum. Thus, a spectrum sharing and energy cooperation scheme is proposed, where the SUs help transfer energy to the PU in the first phase, and in return, the PU allows the SUs to access the spectrum in the second phase. This is particularly beneficial when the PU is energy-limited wireless sensor node or internet of things and the transmitters of SUs are base stations or access points with sufficient energy supply. Without loss of generality, we aim to maximize the minimum data rate among all SUs by jointly optimizing the time- splitting factor between the two phases, the transmission power at the primary transmitter (PT) and the precoding vectors for secondary transmitters (STs) under the minimum data rate requirement of the PU, and the power constraint at each ST. We also guarantee the energy causality constraint at the PT, i.e., the total consumed energy should be no larger than the total available energy. To solve this non-convex problem, we propose an efficient iterative algorithm by applying the successive convex approximation (SCA) and further show that the proposed algorithm is guaranteed to converge. Simulation results are finally presented to show the effectiveness of our proposed scheme.

Degrees of freedom (DoF) of the three-user multiple-input multiple-output (MIMO) broadcast channel (BC) with delayed CSIT was derived for most antenna configurations except for the case of , where transmitter has M antennas and each receiver has N antennas. In this paper, for that problem, we propose an effective scheme for acquiring a higher achievable DoF than the value via existing methods. In the initial transmission phase, we transmit more data symbols than the amount that the receivers can instantaneously decode. Then, we generate auxiliary symbols for decoding the data symbols. Specifically, our scheme introduces an integrated design for the generation of auxiliary symbols. As a result, a higher achievable DoF, i.e., [12MN/(7M+2N)], can be achieved for specific antenna configurations, where .2N <; M <; 2.5N.