Carrier Multiplexing Generalized Space Shift Keying Modulation with Low Decoding Complexity

Since the existing full-rate cooperative transmission schemes have a serious defect in low Bit Error Rate (BER) performance while the existing high-rate cooperative transmission schemes have a serious defect in low spectral efficiency, a distributed high-rate cooperative relay transmission scheme based on full-rate cooperative communication model is proposed in this paper, in which Cyclic Delay Diversity (CDD) technology and Linear Constellation Precoding (LCP) technology are employed. Moreover, the proposed scheme addresses the issue of obtaining maximum spatial and multipath diversity with low decoding complexity and high transmission reliability. The BER performance of the proposed scheme is contrasted to that of the full-rate transmission scheme where better performance is achieved, and is improved when the number of the multipath or the relay nodes increases.

A new rate 1/2 turbo code with short memory 2 is developed in this paper. The proposed turbo code consists of two 4-state parallel concatenated non-punctured systematic rate-2/3 convolutional codes. Using a modified maximum a posteriori (MAP) decoding algorithm working on dual codes, its bit error rate (BER) performance is comparable to that of the classic 16-state turbo code at short block lengths, such as k=1024, while its decoding complexity is less than 1/8 that of the classic 16-state turbo codes; for information block length k=504, its BER performance is better than that of the (1008, 3, 6) LDPC codes with comparable decoding complexity. The dual code decoding algorithm is intrinsically partial parallel and a considerably higher throughput of the turbo decoder can be obtained compared with classic turbo codes consisting of punctured codes. The simulation results show that the proposed turbo code can be a competitive technique for short block length applications.

Multiple Input Multiple Output (MIMO) low complexity receiver which utilizes the compressive sensing detection for Spatial Modulation in large scale MIMO system in order to reduce the system complexity. In conventional MIMO system; huge amount of antennas is used at both ends to exploit the multipath propagation. This system maximizes the throughput performance and data rates are increased but only at the cost of high hardware complexity and increased power-consumption. Spatial Modulation Matching Pursuit (SMMP) is the proposed enhanced CS technique used for the improvement of detection performance. Hence, this paper reviews recent research findings concerning normalized Compressive Sensing (CS) detection algorithm, used for Spatial Modulation (SM) in massive MIMO, to lowers the signal processing complexity, which in result improves the energy efficiency of system against that of conventional MIMO system.This strategy is achieved by involving additional structures and sparsity in which a single transmitter antenna or a subset of it is turned on at each case to transmit a certain data. The subset of antenna which is turned on for transmission depends on approaching data bits. Therefore, the total increase in the spectral efficiency of the system is given as base-two logarithm of whole antennas at the transmitter. It reduces the signal processing load at base station and doesn’t depend upon any synchronization between transmitters. The Spatial Modulation Matching Pursuit used prevents the Inter Channel Interference (ICI) of the system which in result improves the Bit Error Rate (BER) performance than the typical MIMO system.

Multiple input multiple output (MIMO) systems can be designed for two operational modes: to improve bit error rate (BER) or to increase capacity without consuming additional power or bandwidth. In this paper, MIMO space-time-frequency (STF) conjugate two-path transmission orthogonal frequency division multiplexing (OFDM) systems with precoders are presented to combat inter-carrier interference and to adaptively switch between these two modes in mobile fading channels. First, the STF architecture is developed to form a 2 × 1 STF-OFDM system. Second, a conjugate cancellation (CC) two-path transmission scheme is integrated with the STF-OFDM system to form a new 2 × 1 STFCC-OFDM system. This system improves BER without expanding power or bandwidth in comparing with the CC scheme. Third, Walsh–Hadamard (WH) transform is employed as the precoder to form the 2 × 1 WHSTFCC-OFDM system. Finally, a 2 × 2 WHSTFCC-OFDM architecture is designed. It can be used to improve BER or switch to two 2 × 1 WHSTFCC-OFDM systems to increase capacity as needed. Simulations indicate that the 2 × 1 WHSTFCC-OFDM system has the best BER, the STFCC-OFDM system, and the STF-OFDM system follow in order. Similarly, the BER of the 2 × 2 WHSTFCC-OFDM system outperforms the 2 × 1 WHSTFCC-OFDM, and the 2 × 2 STFCC-OFDM system follow in order. All these STFCC- and WHSTFCC-OFDM schemes are simple and backward compatible with the existing OFDM system. They may serve as baseband building blocks in OFDM transceivers and can be adaptively switched between 2 × 1 and 2 × 2 architectures as required for the fourth generation and the future planned fifth generation MIMO systems. This adaptive MIMO system can also be applied to the regular or bad weather environment in the disaster conditions for increasing capacity or enhancing the reliability of the communication system.

To improve the bit error rate (BER) performance of multiple input multiple output (MIMO) systems with low complexity, a three-branch transmission scheme employing 8-weighted-type fractional Fourier transform (8-WFRFT) module is proposed. In the proposed scheme, the original signal is first decomposed into eight sub-signals and then merged into three component signals by the same carrier pattern. The three signals have mathematical constraint relations among themselves that can counteract the channel fading. They are simultaneously transmitted via three independent antennas after delay regulating. At the receiver, an inverse 8-WFRFT module is employed to obtain the estimated original signal by processing the received signal. Then, the bit error rate (BER) performance, transmitting power, transmission rate, power spectrum and computational complexity of the proposed scheme are analysed in detail. Numerical results show that the proposed scheme has a superior performance compared to STBC based three-antenna transmission scheme, in terms of BER performance.

In this paper, we propose a multi-user orthogonal frequency-division multiplexing (OFDM) transmission scheme with partial channel reusing between users, suitable for multiple-input multiple-output (MIMO) systems with not-so-large antenna arrays. The spectrum efficiency is improved at the price of adding multiuser interference (MUI) which can be overcome by the multiplexing gain of MIMO. In addition, we propose to employ the spread spectrum OFDM (SS-OFDM) modulation with the Walsh-Hadamard (WH) codebook for such a multi-user system to further mitigate the MUI. The bit error rate (BER) performance of the proposed scheme in the additive white Gaussian noise (AWGN) channels is derived analytically and then verified through Monte-Carlo simulations. Moreover, the proposed SS-OFDM system with partial bandwidth reuse is compared with the OFDM-based solution in a moderate-scale MIMO system with equal gain combining (EGC) precoding. It is shown that the proposed SS-OFDM MIMO system outperforms the classical OFDM approach in frequency-selective fading channels when the number of transmit antennas remains moderate.

Perfect Space-Time Block Codes (PSTBCs) achieve full diversity, full rate, nonvanishing constant minimum determinant, uniform average transmitted energy per antenna, and good shaping. However, the high decoding complexity is a critical issue for practice. When the Channel State Information (CSI) is available at both the transmitter and the receiver, Singular Value Decomposition (SVD) is commonly applied for a Multiple-Input Multiple-Output (MIMO) system to enhance the throughput or the performance. In this paper, two novel techniques, Perfect Coded Multiple Beamforming (PCMB) and Bit-Interleaved Coded Multiple Beamforming with Perfect Coding (BICMB-PC), are proposed, employing both PSTBCs and SVD with and without channel coding, respectively. With CSI at the transmitter (CSIT), the decoding complexity of PCMB is substantially reduced compared to a MIMO system employing PSTBC, providing a new prospect of CSIT. Especially, because of the special property of the generation matrices, PCMB provides much lower decoding complexity than the state-of-the-art SVD-based uncoded technique in dimensions 2 and 4. Similarly, the decoding complexity of BICMB-PC is much lower than the state-of-the-art SVD-based coded technique in these two dimensions, and the complexity gain is greater than the uncoded case. Moreover, these aforementioned complexity reductions are achieved with only negligible or modest loss in performance.

The free space optical (FSO) communication system has attracted many researchers from different countries, owning to its advantages such as high security, high speed and anti-interference. Among all kinds of the channels of the FSO communication system, the atmosphere channel is very difficult to deal with for two typical disadvantages at least. The one is the scintillation of the optical carrier intensity caused by the atmosphere turbulence and the other is the multipath effect by the optical scattering. A lot of studies have shown that the MIMO (Multiple Input Multiple Output) technology can overcome the scintillation of the optical carrier through the atmosphere effectively. So the background of this paper is a MIMO system which includes multiple optical transmitting antennas and multiple optical receiving antennas. A number of particles such as hazes, water droplets and aerosols exit in the atmosphere widely. When optical carrier meets these particles, the scattering phenomenon is inevitable, which leads to the multipath effect. As a result, a optical pulse transmitted by the optical transmitter becomes wider, to some extent, when it gets to the optical receiver due to the multipath effect. If the information transmission rate is quite low, there is less relationship between the multipath effect and the bit error rate (BER) of the communication system. Once the information transmission rate increases to a high level, the multipath effect will produce the problem called inter symbol inference (ISI) seriously and the bit error rate will increase severely. In order to take the advantage of the FSO communication system, the inter symbol inference problem must be solved. So it is necessary to use the channel equalization technology. This paper aims at deciding a equalizer and designing suitable equalization algorithm for a MIMO free space optical communication system to overcome the serious problem of bit error rate. The reliability and the efficiency of communication are two important indexes. For a MIMO communication system, there are two typical equalization methods. The first method, every receiving antenna has an independent equalizer without the information derived from the other receiving antennas. The second, the information derived from all of the receiving antennas mixes with each other, according to some definite rules, which is called space-time equalization. The former is discussed in this paper. The equalization algorithm concludes training mode and non training mode. The training mode needs training codes transmitted by the transmitter during the whole communication process and this mode reduces the communication efficiency more or less. In order to improve the communication efficiency, the blind equalization algorithm, a non training mode, is used to solve the parameter of the equalizer. In this paper, firstly, the atmosphere channel is described focusing on the scintillation and multipath effect of the optical carrier. Then, the structure of a equalizer of MIMO free space optical communication system is introduced. In the next part of this paper, the principle of the blind equalization algorithm is introduced. In addition, the simulation results are showed. In the end of this paper, the conclusions and the future work are discussed.

– This paper analyses the performance of Multiple Input Multiple Output (MIMO) wireless communication system by combining it with an efficient algorithm Diagonal Reduction (DR). DR is a powerful tool to achieve more efficiently a high performance with less complexity. This paper proposes a DR algorithm in order to reduce its complexity named Greedy Diagonal Reduction (GDR) algorithm which gives reduced complexity with efficient performance at the receiver using the MATLAB communication tool box version 7.0 as a simulation tool. From the simulation results of various reduction algorithms it is observed that, DR can reduce the number of iterations using size reduction operations. Proposed DR algorithm gives identical Bit Error Rate (BER) performance with LLL algorithms when applied to Successive Interference cancellation (SIC) decoding. Greedy DR reduces the computational complexity in Multiple Input Multiple Output systems by improving the efficiency in terms of size reduction operations. Sphere Decoding (SD) technique gives better BER performance on comparing with Successive Interference cancellation decoding technique.

A novel algorithm for decoding a general rate K/N convolutional code based on recurrent neural network (RNN) is described and analysed. The algorithm is introduced by outlining the mathematical models of the encoder and decoder. A number of strategies for optimising the iterative decoding process are proposed, and a simulator was also designed in order to compare the Bit Error Rate (BER) performance of the RNN decoder with the conventional decoder that is based on Viterbi Algorithm (VA). The simulation results show that this novel algorithm can achieve the same bit error rate and has a lower decoding complexity. Most importantly this algorithm allows parallel signal processing, which increases the decoding speed and accommodates higher data rate transmission. These characteristics are inherited from a neural network structure of the decoder and the iterative nature of the algorithm, that outperform the conventional VA algorithm.

In this paper, we propose a new type of code called Trellis-based Quasi-Cyclic (TQC)-LDPC convolutional code, which is a special case of protograph-based LDPC convolutional codes. The proposed TQC-LDPC convolutional code can be derived from any QC-LDPC block code by introducing trellis-based convolutional dependency to the code. The main advantage of the proposed TQC-LDPC convolutional code is that it allows reduced decoder complexity and input granularity (which is defined as the minimum number of input information bits the code requires to generate a codeword) while maintaining the same bit error-rate as the underlying QC-LDPC block code ensemble. We also propose two related power-efficient encoding methods to increase the code rate of the derived TQC-LDPC convolutional code. The newly derived short constraint length TQC-LDPC convolutional codes enable low complexity trellis-based decoders and one such decoder is proposed and described in this paper (namely, QC-Viterbi). The TQC-LDPC convolutional codes and the QC-Viterbi decoder are compared to conventional LDPC codes and Belief Propagation (BP) iterative decoders with respect to bit-error-rate (BER), signal-to-noise ratio (SNR), and decoder complexity. We show both numerically and through hardware implementation results that the proposed QC-Viterbi decoder outperforms the BP iterative decoders by at least 1 dB for same complexity and BER. Alternatively, the proposed QC-Viterbi decoder has 3 times lower complexity than the BP iterative decoder for the same SNR and BER. This low decoding complexity, low BER, and fine granularity makes it feasible for the proposed TQC-LDPC convolutional codes and associated trellis-based decoders to be efficiently implemented in high data rate, next generation mobile systems.

Maximum like-lihood (ML) algorithm is the optimal detection scheme for the data detection of multiple-input multiple-output (MIMO) communication systems, but it has a high complexity in its preprocessing. For good performance and low complexity, a new Grover’s Quantum Search (GS) based data detection algorithm for MIMO system is proposed. It can increase the probability amplitude of solutions while reducing the probability amplitude of non-solutions. By Grover’s iterative process, the probability amplitude of solutions can reach maximum. So it can get the solutions after measurement with a high probability. The simulation results show that the proposed data detection algorithm for MIMO system has a very close to ML based data detection in Bit Error Rate (BER) performance, but it has lower complexity than ML based data detection algorithm.

The implementation of Multiple Input Multiple Output (MIMO) on the Sparse Code Multiple Access (SCMA) can enhance performance in 5G future communication. Low complexity detector for the MIMO-SCMA system to achieve near-optimum bit error rate (BER) performance is still hot topic in this research field. This paper is investigate low complexity MIMO-SCMA detector by combining a joint factor graph (JFG) and sphere decoding (SD) algorithm based on message passing algorithm (MPA) called by SD-JFG-MPA. SD-JFG-MPA is combine n-th single factor graph become one virtual factor graph to deal with MIMO detector. SD algorithm is used to reduce high complexity of the JFG-MPA by calculating possible combination codeword within search radius R SD . SD-JFG-MPA is investigated under Rayleigh channel model with overloading factor 150%. The simulation result shows that complexity and BER performance is determined by a selected radius of SD-JFG-MPA. Optimum performance with less processing time for one bit error on single SCMA when $R_{SD} = \sqrt {E_b} \times 3/2 \times r_{max}$ meanwhile for 2x2 MIMO-SCMA when $R_{SD} = \sqrt {E_b} \times N_{mimo} \times r_{max}$. 2×2 MIMO-SCMA performance is better with 5 dB gap at BER = 10−3 compared to single SCMA.

We consider a slow-fading narrowband multiple-input multiple-output (MIMO) multiple-access channel (MAC) in which multiple users, each equipped with multiple transmit antennas, communicate to a receiver equipped with multiple receive antennas. The users are unaware of the channel state information (CSI) whereas the receiver has perfect CSI and employs a successive group decoder (SGD). We obtain achievable outage probabilities for the case where an outage must be declared simultaneously for all users (common outage) as well as the case where outages can be declared individually for each user (individual outage). We then derive the optimum successive group decoder (OSGD) that simultaneously minimizes the common outage probability and the individual outage probability of each user, over all SGDs of permissible decoding complexity. For each channel realization, the OSGD is also shown to maximize the error exponent of the decodable set of users. An adaptive SGD is derived which not only retains the outage optimality of the OSGD but also minimizes the expected decoding complexity. Asymptotically tight (in the limit of high signal-to-noise ratio (SNR)) affine approximations are then obtained for the weighted sum common and individual outage capacities and the symmetric outage capacity yielded by the OSGD. Limiting expressions for the relevant capacities as the number of users and the number of receive antennas approach infinity are also obtained and it is shown that the OSGD yields symmetric capacity gains commensurate with the decoding complexity allowed. Simulation results with practical low-density parity-check (LDPC) outer codes show that the OSGD offers significantly improved performance at low decoding complexity.

The combination of orthogonal frequency division multiplexing (OFDM) and interleave division multiple access (IDMA), known as OFDM-IDMA, has been proposed as a promising multiple access scheme for wireless communications due to its low decoding complexity and potential of achieving high spectral efficiency. However, most of the work on OFDM-IDMA is in radio frequency (RF) communications scenarios and based on computer simulations. In this paper, we propose OFDM-IDMA over underwater acoustic (UWA) channels with experimental results. We also extend the original OFDM-IDMA to a multiple hydrophones scenario to improve the bit error rate (BER) performance. Experimental results show that with multiple hydrophones, the coded BER performance of OFDM-IDMA approaches zero after only a few iterations, validating the feasibility of our proposed approach over UWA channels.