Low-complexity Detection Algorithm Research Articles

Enhancing Performance of Massive MU-MIMO System With LR-RTS: A Low-Complexity Detection Algorithm

Enhancing Performance of Massive MU-MIMO System With LR-RTS: A Low-Complexity Detection Algorithm

Low complexity detection algorithms based on ADMIN for massive MIMO

This paper proposes the alternating direction method of multipliers-based infinity-norm (ADMIN) with threshold (ADMIN-T) and with percentage (ADMIN-P) detection algorithms, which make full use of the distribution of the signal to interference plus noise ratio (SINR) for an uplink massive MIMO system. The ADMIN-T and ADMIN-P detection algorithms are improved visions of the ADMIN detection algorithm, in which an appropriate SINR threshold in the ADMIN-T detection algorithm and a certain percentage in the ADMIN-P detection algorithm are designed to reduce the overall computational complexity. The detected symbols are divided into two parts by the SINR threshold which is based on the cumulative probability density function (CDF) of SINR and a percentage, respectively. The symbols in higher SINR part are detected by MMSE. The interference of these symbols is then cancelled by successive interference cancellation (SIC). Afterwards the remaining symbols with low SINR are iteratively detected by ADMIN. The simulation results show that the ADMIIN-T and the ADMIN-P detection algorithms provide a significant performance gain compared with some recently proposed detection algorithms. In addition, the computational complexity of ADMIN-T and ADMIN-P are significantly reduced. Furthermore, in the case of same number of transceiver antennas, the proposed algorithms have a higher performance compared with the case of asymmetric transceiver antennas.

Differential space time media‐based modulation system

Differential spatial modulation (DSM) is a multi-antenna differential technology with low power consumption and no demand of channel estimation. It is suitable for communication systems that have fast migration velocity and high requirements for both power consumption and complexity. However, due to the sparse structure and the requirements of differential coding, the spectral efficiency is limited. Therefore, media-based modulation (MBM) technology is introduced into differential system in this work to improve the spectral. A differential space time media-based modulation (DSTMBM) system is proposed. While retaining the inherent advantages of the DSM, the additional bits are transmitted through the radio frequency (RF) mirrors in DSTMBM. Unlike traditional DSM, the transmit antenna of DSTMBM system can be activated multiple times. In addition, a theoretical performance is derived, and a low-complexity (LC) detection algorithm is adopted. Simulation results show that the DSTMBM system has a performance advantage of about 4.5 dB at a high transmission rate compared to traditional DSM systems. Monte Carlo simulation matches the theoretical performance in a wide range. Meanwhile, the LC detection algorithm reduces the complexity by 2–3 orders of magnitude without the bit error rate (BER) performance loss.

Novel K best sphere decoders with higher order modulation for internet of things

SummaryFuture generation communication devices, particularly the Internet of Things (IoTs) demand for low bit error rate (BER) and higher spectral efficiencies. In this context, a low complexity detection algorithm plays a vital role in determining the performance of receivers. In this paper, we have evaluated the performance of low complexity sphere decoders using best algorithm by modifying the conventional sphere decoders into new and sphere decoders. The proposed algorithm enables the sphere decoders to use smaller values of for better performance. Numerical simulation is performed using MATLAB to support the validity of the proposed algorithm in terms of BER and spectral efficiency at higher order modulation techniques such as 1024 quadrature amplitude modulation (QAM) and offset quadrature amplitude modulation (OQAM). Further, we have also analyzed the computational complexity of the proposed algorithm.

Joint estimation and detection method based on turbo equalization framework and VAMP

In this letter, we consider the single-carrier frequency domain equalization (SC-FDE) system, and propose a low-complexity joint symbol detection and channel estimation algorithm based on the recently proposed vector approximate message passing (VAMP). Specifically, we leverage VAMP twice to estimate symbols and channels, respectively, in a turbo-like way. Moreover, this algorithm organically combines the gaussian mixture model (GMM), which can accurately simulate the sparse aggregation characteristics of the channel and effectively suppress inter symbol interference (ISI). The simulation results show that compared with the traditional linear minimum mean square error (LMMSE) estimation receiving algorithm and the existing generalized approximate message passing algorithm (GAMP), the designed receiving algorithm has significant advantages in channel estimation normalized mean square error (NMSE) and bit error ratio (BER) performance, where sharing the same order of complexity.

Low-Complexity Detection Algorithms Applied to FTN-GFDM Systems

New applications for mobile networks are pushing the data rates to higher numbers, requiring new solutions to support the demand for throughput. In urban and dense areas, the use of massive multiple-input multiple-output, high bands in millimeter waves, and ultra-dense networks based on small cells are being used to provide high data rates. However, these solutions are not applicable to the enhanced remote areas communications scenario, where large cells must be deployed using vacant VHF or UHF bands using an opportunistic spectrum allocation approach. In this case, one reasonable solution to increase the overall system data rate is to enhance the waveform spectrum efficiency. This paper proposes a scheme to improve the generalized frequency division multiplexing spectral efficiency by exploiting the faster-than-Nyquist principles in the time and frequency domains without introducing any penalties in terms of bit error rate. This achievement is obtained by under-sampling the time-frequency grid, which results in transmitting more data symbols per waveform sample, while introducing a controlled amount of interference in the transmitted waveform. On the receiver side, low complexity detectors, such as sphere decoder, successive symbol-by-symbol sequence estimation, successive symbol-by-symbol with go-back K sequence estimator, and frequency-domain equalization, can be used to reconstruct the transmitted data. This paper presents the details for adapting the mentioned detectors for the proposed waveform and it also analyzes their performance in terms of bit error rate under different channel models and implementation complexity. From all the detectors considered in this paper, the sphere decoder stands out because it presents an interesting tradeoff between complexity and bit error rate, even in high interference scenarios. Other detection schemes initially proposed for multiple-input multiple-output systems can be adapted to deal with the interference introduced by the faster-than-Nyquist generalized frequency division multiplexing with affordable complexity and acceptable bit error rate performance. Hence, one may conclude that the faster-than-Nyquist generalized frequency division multiplexing is a feasible candidate waveform for the enhanced remote areas communications scenario when high spectrum efficiency is necessary.

Research on PDMA system based on complementary sequence and low complexity detection algorithm

With the intensive deployment of mobile networks and the vigorous development of new multimedia services, video has gradually become the mainstream of cultural consumption. The contradiction between the proliferation of video data services and the scarcity of spectrum resources has brought great challenges to the current network resource allocation. Non-orthogonal multiple access (NOMA) can be used to solve this problem by signal superposition and spectrum multiplexing to improve system access capability. As a new type of joint optimization design of transmitter and receiver side, PDMA has high research value. In this paper, a framework of PDMA video transmission system based on H.264 video compression coding (HVC-PDMA) is proposed. Poly complementary sequence (PCS) spread spectrum coding is performed on the transmission codebook in order to improve the transmission accuracy. Meanwhile, a low complexity serial sphere compensated Max-log MPA (SSCM-MPA) algorithm is proposed to reduce the complexity of the multi-user detection algorithm. Simulation results show that the PCS spread spectrum can improve system throughput and peak signal-to-noise ratio (PSNR) while reducing bit error rate (BER). SSCM-MPA algorithm can greatly reduce the complexity and improve the transmission efficiency.

Massive Coded-NOMA for Low-Capacity Channels: A Low-Complexity Recursive Approach

In this paper, we present a low-complexity recursive approach for massive and scalable code-domain nonorthogonal multiple access (NOMA) with applications to emerging low-capacity scenarios. The problem definition in this paper is inspired by three major requirements of the next generations of wireless networks. Firstly, the proposed scheme is particularly beneficial in low-capacity regimes which is important in practical scenarios of utmost interest such as the Internet-of-Things (IoT) and massive machine-type communication (mMTC). Secondly, we employ code-domain NOMA to efficiently share the scarce common resources among the users. Finally, the proposed recursive approach enables code-domain NOMA with low-complexity detection algorithms that are scalable with the number of users to satisfy the requirements of massive connectivity. To this end, we propose a novel encoding and decoding scheme for code-domain NOMA based on factorizing the pattern matrix, for assigning the available resource elements to the users, as the Kronecker product of several smaller factor matrices. As a result, both the pattern matrix design at the transmitter side and the mixed symbols' detection at the receiver side can be performed over matrices with dimensions that are much smaller than the overall pattern matrix. Consequently, this leads to significant reduction in both the complexity and the latency of the detection. We present the detection algorithm for the general case of factor matrices. The proposed algorithm involves several recursions each involving certain sets of equations corresponding to a certain factor matrix. We then characterize the system performance in terms of average sum rate, latency, and detection complexity. Our latency and complexity analysis confirm the superiority of our proposed scheme in enabling large pattern matrices. Moreover, our numerical results for the average sum rate show that the proposed scheme provides better performance compared to straightforward code-domain NOMA with comparable complexity, especially at low-capacity regimes.

Optimality of Linear MIMO Detection for 5G Systems via 1-Opt Local Search

Multiple input multiple output (MIMO) symbol detection problem belongs to non-deterministic polynomial acceptable hard combinatorial optimization (CO) class. One of the key trials in design of MIMO scheme is to develop a low complexity detection algorithm without much compromise in performance. Detection approaches proposed in the literature can be split into non-linear and linear algorithms. Vertical Bell-Labs Layered Space Time (V-BLAST) and Sphere Decoder (SD) are non-linear methods used for extracting transmitted data; whereas, Zero-Forcing (ZF) and Minimum Mean Square Error (MMSE) detections are comparatively in complex and effectual linear techniques. In this work, the heuristic 1-Opt local search method used for solving computationally hard combinatorial optimization problems is applied to the ZF and MMSE detection algorithms. First, simple MIMO decoding using ZF and MMSE is accomplished to find the estimated symbol then the transmitted symbol is calculated using the heuristic 1-opt approach by means of the estimated symbol. Simulation results demonstrate that 1-opt search when applied to the ZF and MMSE displays better bit error rate (BER) performance than the simple ZF and MMSE detectors. It is also verified through simulations that the proposed 1-Opt based detectors display better BER performance as compared to the complex nonlinear VBLAST and SD at considerably reduced complexity. Hence, the proposed detectors are appropriate for effective hardware implementations.

Downlink Synchronization for OTFS-Based Cellular Systems in High Doppler Environments

This paper proposes a downlink synchronization and cell identity (CID) estimation technique for cellular systems based on orthogonal time-frequency space (OTFS). In the proposed technique, each base station (BS) transmits one detection preamble (DP) and two OTFS symbols (pilot and secondary-CID (SCID) signal (SS)). The DP based on a linear frequency-modulated (LFM) waveform, called proposed-LFM (pLFM), carries the primary-CID (PCID) for symbol timing (ST) synchronization, whereas the SS based on the Zadoff-Chu (ZC) sequence mapped in the delay-Doppler domain carries the SCID. The pLFM is obtained by discretizing the LFM waveform, increasing the frequency sweeping parameter beyond the limit of the operational bandwidth, and incorporating the PCID into the LFM waveform. The autocorrelation and cross-correlation functions of the pLFM are analyzed to examine its correlation properties under the influence of a high Doppler shift. To reduce the undesirable correlation properties (side peak and time ambiguity), a receiver processing (RP) scheme is developed for the pLFM. It is found that the pLFM with RP is suitable for the DP design because it can provide an accurate ST in high-mobility scenarios. In addition, the influence of OTFS modulation on the ZC sequence is derived and a low-complexity detection algorithm based on message passing is applied to detect SCID at the user equipment. The simulation results demonstrate that the proposed downlink synchronization and CID estimation techniques are suitable for OTFS-based cellular systems in high-Doppler environments.

Constant Weight Space-Time Codes for Dimmable MIMO-VLC Systems

Visible light communication(VLC), which combines communication and illumination, is regarded as a potential wireless communication. For illumination requirements of VLC systems, dimming control is a significant function. Many schemes have been proposed for multi-input multi-output (MIMO) VLC systems or dimmable VLC systems, but few schemes combine the two. The dimming control scheme that has been proposed for MIMO-VLC systems in the reference still has a probability for improvement in spectral efficiency and error performance. This paper proposes a dimming control scheme that utilizes the constant weight space-time codes (CWSTC) to improve spectral efficiency and error performance for MIMO-VLC systems. Simultaneously, we also present the codeword structure and a low implementation complexity detection algorithm for the scheme. Finally, performance analysis and simulation results provide comparisons between the proposed scheme and other existing dimming control schemes.

Hybrid Transceiver Design for Beamspace MIMO-NOMA in Code-Domain for MmWave Communication Using Lens Antenna Array

As a hybrid MIMO architecture, beamspace multiple input multiple output (MIMO) can significantly reduce the number of required radio frequency (RF) chains in millimeter wave (mmWave) massive MIMO systems without obvious performance loss, in which, however, the number of users supported cannot be larger than that of RF chains. To break this fundamental limit, we introduce the concept of code-domain non-orthogonal multiple access (NOMA) into beamspace MIMO. A beam selection scheme is proposed first to maximize the sum-rate by utilizing the quasi-orthogonality of the beamspace channel. Furthermore, a low-complexity detection algorithm is developed to realize the transceiver design in mmWave communications using lens antennas. Finally, numerical results of the decoding complexity at receiver side are analyzed. Simulation results show that the proposed beamspace MIMO-NOMA in code domain can achieve higher spectrum and energy efficiency compared with the existing beamspace MIMO.

A Robust Hybrid Iterative Linear Detector for Massive MIMO Uplink Systems

Fifth-generation (5G) communications system is commercially introduced by several mobile operators where sub-6 GHz bands are the backbone of the 5G networks. A large-scale multiple-input multiple-output (MIMO), or massive MIMO (mMIMO), technology has a major impact to secure high data rate, high spectral efficiency, and quality of service (QoS). It could also have a major role in the beyond-5G systems. A massive number of antennas seek advanced signal processing to detect and equalize the signal. However, optimal detectors, such as the maximum likelihood (ML) and maximum posterior (MAP), are not desirable in implementation due to extremely high complexity. Therefore, sub-optimum solutions have been introduced to obtain and guarantee enough balance between the performance and the computational complexity. In this paper, a robust and joint low complexity detection algorithm is proposed based on the Jacobi (JA) and Gauss–Seidel (GS) methods. In such iterative methods, the performance, complexity, and convergence rate are highly dependent on the initial vector. In this paper, initial solution is proposed by exploiting the benefits of a stair matrix to obtain a fast convergence rate, high performance, and low complexity. Numerical results show that proposed algorithm achieves high accuracy and relieve the computational complexity even when the BS-to-user-antenna ratio (BUAR) is small.

A Rising Edge-Based Detection Algorithm for MIMO Molecular Communication

In this letter, we propose a low-complexity detection algorithm for multi-input-multi-output (MIMO) molecular communication (MC). By virtue of a rising edge in received signals, this detection algorithm is capable of recovering the information bits in MIMO-MC systems. From an engineering point of view, this algorithm can significantly eliminate the impact of inter-symbol interference. It has also proven itself useful for dealing with the received signal from the MIMO-MC testbed with sufficiently low bit error rate (BER) or even an error-free performance. Moreover, in terms of BER performance, this algorithm outperforms existing detection algorithms for single-input single-output MC systems.

Low-Complexity Adaptive Signal Detection for Mobile Molecular Communication.

Currently, most of the researches in molecular communication (MC) domain focus on the static MC scenarios. However, some envisioned important MC applications require mobile MC system. The investigation on mobile MC, especially the signal detection of mobile MC is limited. This work considers the problem of signal detection for mobile MC scenarios where the receiver nano-machine performs random movement. Due to the random movement of the receiver, the channel impulse response (CIR) changes over time which makes the received signal stochastic and complicated. This further complicates the signal detection in mobile MC and leads to that the state-of-the-art signal detection schemes for static MC scenarios fail for the mobile MC scenarios. To solve this issue, an adaptive detection scheme has been proposed by our group previously, based on dynamic estimation of the stochastically varying distance between the transmitter and receiver and the reconstruction of CIR in each interval. However, its computational complexity is high. Limited capability of current nano-machines desire low-complexity detection algorithm. In this work, we further propose an adaptive detection scheme for mobile MC with a low computational complexity by utilizing the local convex property of the CIR. With on-off keying (OOK) modulation, the signal of symbol "1" presents local convex property while that of symbol "0" presents local concave property. The convexity extent varies with the stochastic distance. A simple indicator, local maximum convexity is proposed which adapts to the stochastic distance. By comparing the adaptive indicator with an adaptive threshold within each symbol interval, the signal is detected without the need to estimate the stochastically changing distance or to reconstruct the CIR. Therefore, the computational load is effectively reduced. Numerical simulations are performed to evaluate the proposed scheme. The results show that the proposed scheme achieves good detection accuracy with low computational complexity and it could be a promising detection scheme for mobile MC scenarios.

Low-Complexity Differential Spatial Modulation Schemes for a Lot of Antennas

Spatial modulation (SM) uses a single antenna for transmission each time to avoid synchronization and interferences among transmitter antennas, and differential SM (DSM) is a kind of SM technique that does not need pilot symbols and channel estimation. The original noncoherent detection for DSM is very complicated, so various low-complexity detectors have been proposed. However, they are still too complicated to be applied to DSM with many transmitter antennas. In this paper, low-complexity DSM schemes for dozens or hundreds of transmitter antennas are designed. Two bit-mapping schemes are proposed: one is group arrangement for maximizing data rates, and the other is full mapping so that DSM can be easily detected at the receiver. A low-complexity detection algorithm that is less complicated than all existing fixed-complexity detectors is proposed as well. In addition, two detection strategies for the proposed bit mapping methods are proposed. Simulation results show that the proposed low-complexity DSM schemes have satisfactory error performance.

Fast Scalable Architecture of a Near-ML Detector for a MIMO-QSM Receiver

This paper presents a proposal for an architecture in FPGA for the implementation of a low complexity near maximum likelihood (Near-ML) detection algorithm for a multiple input-multiple output (MIMO) quadrature spatial modulation (QSM) transmission system. The proposed low complexity detection algorithm is based on a tree search and a spherical detection strategy. Our proposal was verified in the context of a MIMO receiver. The effects of the finite length arithmetic and limited precision were evaluated in terms of their impact on the receiver bit error rate (BER). We defined the minimum fixed point word size required not to impact performance adversely for n T transmit antennas and n R receive antennas. The results showed that the proposal performed very near to optimal with the advantage of a meaningful reduction in the complexity of the receiver. The performance analysis of the proposed detector of the MIMO receiver under these conditions showed a strong robustness on the numerical precision, which allowed having a receiver performance very close to that obtained with floating point arithmetic in terms of BER; therefore, we believe this architecture can be an attractive candidate for its implementation in current communications standards.

Design of Differential Spatial Modulation Cooperative System Based on Complementary Code

The traditional differential spatial modulation (DSM) cooperative system overcomes the interference between the antennas by the orthogonality of direct sequence-code division multiple access spreading code. But the spreading sequences they used have the following undesirable properties: the non-zero sidelobes of auto-correlation functions will result in severe multi-path interference, and the non-zero values of cross-correlation functions will result in serious multiple access interference. In this paper, we propose a novel DSM cooperative system scheme to overcome this limitation. In our proposed scheme, the anti-interference characteristic of the system is improved by replacing the traditional spreading codes with complementary codes (CCs) at the transmitter. The DSM signal system constructed by using a multi-symbol dispersion matrix at the transmission relay end can improve the system transmission efficiency and avoid the channel interference. At the receiver, in order to reduce the high computational complexity of traditional maximum likelihood detection algorithm, a low-complexity detection algorithm based on the column search is proposed. The simulation results show that the bit error rate performance of DSM cooperative system based on the CC is superior to the traditional DSM cooperative system based on spreading codes. Meanwhile, the system performance with complete CCs is superior to that with the other CCs, and its implementation complexity is lower.

Optimized Cooperative Finite-Alphabet Two-Way Relaying Strategy for Indoor Visible Light Communication Systems

In this paper, we propose an optimized cooperative finite-alphabet relaying strategy for two-way relay visible light communication (VLC) systems, in which the relay node has its own information to be transmitted. In the multiple access (MAC) stage, for fixed transmission bit rate of each user, an optimal power control strategy is developed to manage the non-negative finite-alphabet multiuser interference. Under this strategy, it is proved that the received signal constitutes an equally spaced pulse amplitude modulation constellation, which admits low-complexity maximum likelihood detection. In addition, for given overall transmission bit rate of MAC stage, we derive a closed-form solution for optimal bit loading to further improve the energy-efficiency of MAC stage. In the broadcast stage, owing to the fact that each buffer-aided user node knows the signals transmitted to the relay node in the MAC stage, we design a buffer-aided optimal encoding constellation, which can obtain significant performance gains. Intended for this transmitted constellation, we develop two low-complexity detection algorithms. Both the analytical results and computer simulations demonstrate that our proposed design has substantial performance advantage over the currently available time orthogonal transmission scheme for this application.

Optimum Low-Complexity Decoder for Spatial Modulation

In this paper, a novel low-complexity detection algorithm for spatial modulation (SM), referred to as the minimum-distance of maximum-length (m-M) algorithm, is proposed and analyzed. The proposed m-M algorithm is a smart searching method that is applied for the SM tree-search decoders. The behavior of the m-M algorithm is studied for three different scenarios: i) perfect channel state information at the receiver side (CSIR), ii) imperfect CSIR of a fixed channel estimation error variance, and iii) imperfect CSIR of a variable channel estimation error variance. Moreover, the complexity of the m-M algorithm is considered as a random variable, which is carefully analyzed for all scenarios, using probabilistic tools. Based on a combination of the sphere decoder (SD) and ordering concepts, the m-M algorithm guarantees to find the maximum-likelihood (ML) solution with a significant reduction in the decoding complexity compared to SM-ML and existing SM-SD algorithms; it can reduce the complexity up to 94% and 85% in the perfect CSIR and the worst scenario of imperfect CSIR, respectively, compared to the SM-ML decoder. Monte Carlo simulation results are provided to support our findings as well as the derived analytical complexity reduction expressions.