Low-complexity Detection Method Research Articles

Affine Frequency Division Multiplexing for Next Generation Wireless Communications

Affine Frequency Division Multiplexing (AFDM), a new chirp-based multicarrier waveform for high mobility communications, is introduced here. AFDM is based on discrete affine Fourier transform (DAFT), a generalization of discrete Fourier transform, which is characterized by two parameters that can be adapted based on the Doppler spread of doubly dispersive channels. First, we derive the explicit input-output relation in the DAFT domain showing the effect of AFDM parameters in the input-output relation. Second, we show how the DAFT parameters underlying AFDM have to be set so that the resulting DAFT domain impulse response conveys a full delay-Doppler representation of the channel. Then, we show analytically that AFDM can achieve the optimal diversity order in doubly dispersive channels, where optimal diversity order refers to the number of multipath components separable in either the delay or the Doppler domain, due to its full delay-Doppler representation. Furthermore, we present a low complexity detection method taking advantage of zero-padding. We also propose an embedded pilot-aided channel estimation scheme for AFDM, in which both channel estimation and data detection are performed within the same AFDM frame. Finally, simulations corroborate the validity of our analytical results and show the significant performance gains of AFDM over state-of-the-art multicarrier schemes in high mobility scenarios.

Reconfigurable Intelligent Surface-Aided Quadrature Reflection Modulation for Simultaneous Passive Beamforming and Information Transfer

Reflection modulation based on reconfigurable intelligent surface (RIS) is considered to be a promising information transfer mechanism, which does not require any additional radio frequency chains. However, existing reflection modulation schemes consider manipulating the ON/OFF states of RIS elements, which may result in some power loss. In this paper, we propose a new scheme, called RIS-aided quadrature reflection modulation (RIS-QRM), for better utilizing the reflection power in RIS-aided downlink multiple-input single-output (MISO) wireless systems. To this end, RIS-QRM partitions the RIS elements into two subsets in order to reflected the incident signals towards two orthogonal directions by using passive beamforming and encodes its local data onto the two partitions. A closed-form expression for the unconditional pairwise error probability of RIS-QRM in Rician fading is derived assuming maximum-likelihood detection at the receiver. Moreover, a low-complexity detection method that decouples the joint search of the constellation symbol and the RIS element partition is proposed. Computer simulation results corroborate the effectiveness of RIS-QRM and validate the analytical results. It is shown that RIS-QRM improves the error performance of the additional bits delivered by the RIS without deteriorating the error performance of the bits modulated on the constellation symbol, as compared to ON/OFF-based RIS-aided schemes.

Orthogonal Time Sequency Multiplexing Modulation: Analysis and Low-Complexity Receiver Design

This paper proposes orthogonal time sequency multiplexing (OTSM), a novel single carrier modulation scheme that places information symbols in the delay-sequency domain followed by a cascade of time-division multiplexing (TDM) and Walsh-Hadamard sequence multiplexing. Thanks to the Walsh Hadamard transform (WHT), the modulation and demodulation do not require complex domain multiplications. For the proposed OTSM, we first derive the input-output relation in the delay-sequency domain and present a low complexity detection method taking advantage of zero-padding. We demonstrate via simulations that OTSM offers high performance gains over orthogonal frequency division multiplexing (OFDM) and similar performance to orthogonal time frequency space (OTFS), but at lower complexity owing to WHT. Then we propose a low complexity time-domain channel estimation method. Finally, we show how to include an outer error control code and a turbo decoder to improve error performance of the coded system.

Performance Analysis of Orbital Angular Momentum (OAM): A 6G Waveform Design

Next-generation communication systems are required to be efficient in power and spectrum usage. In this direction, novel spatial multiplexing techniques, such as orbital angular momentum (OAM), in contrast to frequency multiplexing, such as orthogonal frequency division multiplexing (OFDM), are regarded to uphold potential advantages. This letter investigates OAM and OFDM along with their emerging variants with index modulation (IM) in MIMO configuration. In this letter, these techniques are implemented for different cell distances mainly for single user cases. The bit error rate (BER) performance analysis is then carried out on a comparative scale. Moreover, Maximum likelihood and least square-based receiver techniques are presented for low complexity detection methods. The strengths and weaknesses of these techniques are analyzed through extensive MATLAB simulations for different Signal-to-Noise Ratios (SNRs).

A Differential Modulation Scheme for Metasurface-Based Terahertz Communications

Metasurface-based terahertz (THz) modulators, which carry information by changing the spatial pattern of the metasurface at every symbol time, are an important component to establish low-cost low-energy–consuming THz communication systems. This paper proposes a differential spatial THz modulation (DSTM) scheme for metasurface-assisted THz communications. In DSTM, the metasurface pattern activation orders are employed to carry information, instead of the metasurface patterns themselves. In this way, the DSTM receiver can perform differential detection without knowing the metasurface response to incident THz signals and the channel state information. The proposed DSTM scheme is applicable to all kinds of metasurfaces enabling THz communications, including transmissive metasurfaces and reflective metasurfaces. For high-rate DSTM systems, we propose an efficient bits-to-activation-order mapping method and a low-complexity detection method. Simulations are conducted to demonstrate the performance of the proposed scheme. It is shown that the proposed scheme pays acceptable penalty compared to the non-differential modulation scheme with coherent detection, which needs to know the metasurface response to the incident signals as well as all the channel state information.

NOMA-aided generalized pre-coded quadrature spatial modulation for downlink communication systems

Generalised pre-coding quadrature spatial modulation (GPQSM) is recently proposed to increase the spectral efficiency (SE) of GPSM, which extends the transmitted symbols into in-phase/quadrature domains. In this paper, a novel scheme named non-orthogonal multiple access (NOMA)-aided GPQSM (NOMA-GPQSM), which incorporates the GPQSM scheme into the multi-user communication networks with assist of NOMA, is proposed to further improve the SE and system performance. In NOMA-GPQSM, one base station (BS) is set to serve K users, where user 1 is closest to the BS, and user K is farthest from the BS. In addition, a low-complexity detection method is proposed to reduce the high detection complexity of the maximum-likelihood (ML) detection in successive interference cancellation (SIC) method for all users by NOMA-GPQSM. The theoretical analysis of the BER performance for all users is also derived. Simulation results show that near users achieve relatively good performance, and far users achieve acceptable performance by adjusting power factors for all users in NOMA-GPQSM.

A low complexity detection method for video data discontinuity implemented on SoC-FPGA by using pixel location prediction scheme

Image/video processing in real-time is always in high demand for the quality of video. There are several factors which cause the loss of the video content, such as the type of transmission, missing data and especially data switch. Data switch generally occurs in the alternation of the video signal, which can cause the discontinuity of data during the video data stored in buffer or memory. The current method which adopts frame difference for detecting this issue may consume many resources and memory footprint. This paper presents a method which uses the video pixel prediction to detect the freezing event. The method is implemented with a video system which employs the System-on-chip (SoC) architecture with Field Programmable Gate Array (FPGA) and other components including DDR3 ram, flash, and exchange interfaces as the main processing platform that prevents this problem through freezing detection. The result of evaluation shows that the accuracy of the proposed method is above 99%, in terms of saving more logic usage and reducing the footprint of the memory on the video system.

Strict parity symmetric prolate spheroidal wave functions signal construction and low complexity detection method

Aiming at solving the problem of high signal processing and detection complexity of prolate spheroidal wave functions (PSWFs), we propose a time domain strict parity symmetry PSWFs signal construction method, based on the characteristics of PSWFs with the same parity symmetry after linear operation. According to the characteristics that the PSWFs of the same parity symmetry have the same orthogonality in the half-symbol period and the whole symbol period, we propose a PSWFs signal detection method based on the parity characteristics, which groups processing of odd symmetric and even symmetric signals and detects PSWFs signal in the half-symbol period signal to reduce the number of signal solutions for participating in the operation. Compared with the coherent detection method, theoretical and numerical analyses show that the proposed signal detection method can reduce the computational complexity from $O(NQ)$ to $O(NQ/2)$ (i.e., about 50%) without reducing the system error performance.

A Grouped Pre-Coding Aided Spatial Modulation for MIMO Systems

Pre-coding aided spatial modulation (PSM) is a recently introduced concept that achieves low complexity and low cost at the receiver. However, it is only suitable for the symmetric or under-determined system due to the utilization of the linear pre-coding. In this paper, a novel PSM-based transmission strategy termed as grouped pre-coding aided spatial modulation (group PSM) is proposed for the over-determined MIMO system where the number of receive antennas is larger than the number of transmit antennas. In our group PSM scheme, the receive antennas are equally divided into several groups. A single receive antenna group is selected during each time slot and the index of the receive antenna group is used for conveying extra information bits. We design a low complexity detection method for the proposed scheme and derive the bit error rate expression. To further improve the performance of group PSM, we propose a power allocation method, where the power allocated for each receive antenna group is optimized based on maximizing the minimum Euclidean distance between received group PSM signal constellations. We also generalize our group PSM scheme in order to improve the multiplexing gain and flexibility, where a particular subset of receive antenna groups is activated so as to convey more information bits. Our simulation results validate the accuracy of the theoretical analysis and demonstrate that both the proposed group PSM and generalized group PSM schemes achieve good performance and significantly increase the scalability of PSM in practice.

Low-Complexity Detection for Index Modulation Multiple Access

Index modulation multiple access (IM-MA) is recently proposed to exploit the IM concept to the uplink multiple access system, where multiple users transmit their own signals via the selected time slots. However, the computational complexity of the optimal maximum-likelihood (ML) detection in IM-MA is tremendously high when the number of users or time slots is large. In this letter, we propose a low-complexity detection method for IM-MA, which is inspired by the log likelihood ratio (LLR) algorithm. In addition, because of the heavy search burden for all LLR values, we further propose a suboptimal method to determine the permutation set, which records the number of users allocated to each time slot. Simulation results and the complexity analysis verify that the proposed detection performs closely to the optimal ML detection with reduced computational complexity.

Soft-Output Detection Methods for Sparse Millimeter-Wave MIMO Systems With Low-Precision ADCs

The use of low-precision analog-to-digital converters (ADCs) is a low-cost and power-efficient solution for a millimeter wave (mmWave) multiple-input multiple-output (MIMO) system operating at sampling rates higher than a few Gsample/sec. This solution, however, can make significant frame-error-rates (FERs) degradation due to inter-subcarrier interference when applying conventional frequency-domain equalization techniques. In this paper, we propose computationally-efficient yet near-optimal soft-output detection methods for the coded mmWave MIMO systems with low-precision ADCs. The underlying idea of the proposed methods is to construct an extremely sparse inter-symbol-interference (ISI) channel model by jointly exploiting the delay-domain sparsity in mmWave channels and a high quantization noise caused by low-precision ADCs. Then we harness this sparse channel model to create a trellis diagram with a reduced number of states or a factor graph with very sparse edge connections. Using the reduced trellis diagram, we present a soft-output detection method that computes the log-likelihood ratios (LLRs) of coded bits by optimally combining the quantized received signals obtained from multiple receive antennas using a forward-and-backward algorithm. To reduce the computational complexity further, we also present a low-complexity detection method using the sparse factor graph to compute the LLRs in an iterative fashion based on a belief propagation algorithm. Simulations results demonstrate that the proposed soft-output detection methods provide significant FER gains compared to the existing frequency-domain equalization techniques in a coded mmWave MIMO system using one- or two-bit ADCs.

A Precoding Scheme for Eliminating Data Identification Problem in Single Carrier System Using Data-Dependent Superimposed Training

In single carrier (SC) systems using a data-dependent superimposed training (DDST) scheme, the data-induced interference that occurs during channel estimation is eliminated, but at the expense of data distortion. This distortion causes a data identification problem (DIP), in which the data sequence cannot be uniquely identified at the receiver end. Accordingly, the present study proposes a precoding scheme which solves the DIP in SC systems using DDST. Five design criteria are derived for the precoding matrix in order to eliminate DIP, achieve frequency diversity, maintain a low peak-to-average power ratio (PAPR), and minimize the receiver complexity. In addition, a low-complexity detection method is proposed for reducing the search space of the detection process. The simulation results show that the proposed precoding scheme successfully eliminates the DIP in traditional DDST schemes while maintaining the same PAPR as that of the traditional SC systems based on DDST.

Diversity embedded rate configurable GSM and a low complexity detection method

This paper presents an energy efficient transmission method that is suitable for emerging large scale MIMO scenario, by combining space time coding and spatial multiplexing with GSM. The proposed Diversity Embedded SM (DESM) provides required Quality of Service (QoS) for a high priority data and at the same time maintains a fair transmission rate by spatial multiplexing a low priority data. Only limited feedback is required and the system can be configured for different diversity/non-diversity stream rates, as per the required QoS. Utilizing some peculiarities of the channel matrix of the system, a QR decomposition based detection method that requires only four receiving antennas is shown to have good performance. The computational complexity of detection is less compared to the existing GSM detection schemes, for reasonable number of transmit and active antennas. The effect of incorporating diversity on the rate of the system is also analyzed.

Distributed Uplink Reception in Cloud Radio Access Networks: A Linear Coding Approach

This paper considers an uplink cloud radio access network (C-RAN), in which L antenna terminals (ATs) are connected to a central process (CP) via digital error-free links of a finite-capacity R 0 , and serves K user terminals. In this network, novel low-complexity detection methods at the CP are proposed by incorporating a lattice-quantize-and-forward (LQF) framework, which converts the C-RAN into an equivalent finite-field multipleinput-multiple-output (FF-MIMO) channel. In particular, under this equivalent FF single-input-multiple-output channel, an optimal receive combining method is presented by using a simple repetition code. In addition, using linear block codes, a low-complexity detection method is presented for the equivalent FF-MIMO channel. Finally, by simulations, it is demonstrated that the proposed detection method combined with the LQF framework provides high achievable sum rates for uplink C-RANs especially when a lot of low-cost ATs are deployed.

Compressive Random Access With Coded Sparse Identification Vectors for MTC

In this paper, we study a compressive random access scheme that allows the active device identification with unique sparse identification sequences in machine-type communications to support a number of devices. Since the performance of active device identification can be easily degraded by the background noise as well as distortion by frequency-selective fading channels due to the sparsity of identification sequences, we propose a channel coding approach for sparse identification sequences and derive a low-complexity method for maximum likelihood decoding. Based on the proposed channel coding approach, we can significantly improve the performance of active device identification. We also consider a low-complexity detection method to detect signals transmitted with sparse identification sequences and derive a closed-form expression for the bit error rate.

Spatial Lattice Modulation for MIMO Systems

This paper proposes spatial lattice modulation (SLM), a spatial modulation method for multipleinput-multiple-output (MIMO) systems. The key idea of SLM is to jointly exploit spatial, in-phase, and quadrature dimensions to modulate information bits into a multi-dimensional signal set that consists oflattice points. One major finding is that SLM achieves a higher spectral efficiency than the existing spatial modulation and spatial multiplexing methods for the MIMO channel under the constraint ofM-ary pulseamplitude-modulation (PAM) input signaling per dimension. In particular, it is shown that when the SLM signal set is constructed by using dense lattices, a significant signal-to-noise-ratio (SNR) gain, i.e., a nominal coding gain, is attainable compared to the existing methods. In addition, closed-form expressions for both the average mutual information and average symbol-vector-error-probability (ASVEP) of generic SLM are derived under Rayleigh-fading environments. To reduce detection complexity, a low-complexity detection method for SLM, which is referred to as lattice sphere decoding, is developed by exploiting lattice theory. Simulation results verify the accuracy of the conducted analysis and demonstrate that the proposed SLM techniques achieve higher average mutual information and lower ASVEP than do existing methods.

Efficient detection methods for amplify-and-forward relay-aided device-to-device systems with full-rate space-time block code

Relay-aided device-to-device (D2D) communication is a promising technology for the next-generation cellular network. We study the transmission schemes for an amplify-and-forward relay-aided D2D system which has multiple antennas. To circumvent the prohibitive complexity problem of traditional maximum likelihood (ML) detection for full-rate space-time block code (FSTBC) transmission, two low-complexity detection methods are proposed, i.e., the detection methods with the ML-combining (MLC) algorithm and the joint conditional ML (JCML) detector. Particularly, the method with the JCML detector reduces detection delay at the cost of more storage and performs well with parallel implementation. Simulation results indicate that the proposed detection methods achieve a symbol error probability similar to that of the traditional ML detector for FSTBC transmission but with less complexity, and the performance of FSTBC transmission is significantly better than that of spatial multiplexing transmission. Diversity analysis for the proposed detection methods is also demonstrated by simulations.

A low complexity detection algorithm for m-QAM in spatial modulation systems

This paper proposes a low complexity detection method for M-QAM (M-ary quadrature amplitude modulation) in spatial modulation (SM) systems. The new method utilizes the thought of constellation layering to modify constellation points search mode in QAM, which reduces the calculated amount significantly, and the total complexity will not increase with the size of constellation linearly. Simulation results show that the method can work well in high order QAM transmission systems. The novel method provides a significant reduction in computational complexity while keeping the near-optimal bit-error-rate (BER) performance.

Low-Complexity MIMO Detection: A Mixture of Basic Techniques for Near-Optimal Error Rate

The research of finding better ways for multiple-input multiple-output signal detection is important and still goes on. In this brief, a low-complexity detection method mainly with basic and hardware-friendly operations, i.e., reduced-complexity zero forcing, successive interference cancelation, and single-symbol maximum likelihood detection with $M$ - algorithm, is proposed. Essentially, this detection method has fixed complexity and can achieve near-optimal error-rate performance with affordable complexity in many cases. Results show that, in terms of giving a good tradeoff between the implementation complexity and error rate, the proposed low-complexity detection scheme can remarkably outperform some state-of-the-art counterparts, including the conventional ML detector employing QR-decomposition and $M$ - algorithm and fixed-complexity sphere decoder, and owns an error rate very close to that of the optimal one.

Sparse index multiple access for multi-carrier systems with precoding

In this paper, we consider subcarrier-index modulation (SIM) for precoded orthogonal frequency division multiplexing (OFDM) with a few activated subcarriers per user and its generalization to multi-carrier multiple access systems. The resulting multiple access is called sparse index multiple access (SIMA). SIMA can be considered as a combination of multi-carrier code division multiple access (MC-CDMA) and SIM. Thus, SIMA is able to exploit a path diversity gain by (random) spreading over multiple carriers as MC-CDMA. To detect multiple users' signals, a lowcomplexity detection method is proposed by exploiting the notion of compressive sensing (CS). The derived low-complexity detection method is based on the orthogonal matching pursuit (OMP) algorithm, which is one of greedy algorithms used to estimate sparse signals in CS. From simulation results, we can observe that SIMA can perform better thanMC-CDMA when the ratio of the number of users to the number of multi-carrier is low.