Non-orthogonal multiple access (NOMA), which combines multiple user signals and transmits the combined signal over one channel, can achieve high spectral efficiency for mobile communications. However, combining the multiple signals can lead to degradation of bit error rates (BERs) of NOMA under severe channel conditions. In order to improve the BER performance of NOMA, this paper proposes a new NOMA scheme based on orthogonal space-time block codes (OSTBCs). The proposed scheme transmits several multiplexed signals over their respective orthogonal time-frequency channels, and can gain diversity effects due to the orthogonality of OSTBC. Furthermore, the new scheme can detect the user signals using low-complexity linear detection in contrast with the conventional NOMA. The paper focuses on the Alamouti code, which can be considered the simplest OSTBC, and theoretically analyzes the performance of the linear detection. Computer simulations under the condition of the same bit rate per channel show that the Alamouti code based scheme using two channels is superior to the conventional NOMA using one channel in terms of BER performance. As shown by both the theoretical and simulation analyses, the linear detection for the proposed scheme can maintain the same BER performance as that of the maximum likelihood detection, when the two channels have the same frequency response and do not bring about any diversity effects, which can be regarded as the worst case.

The automatic analysis of retinal fundus images is of great significance in large-scale ocular pathologies screening, of which optic disc (OD) location is a prerequisite step. In this paper, we propose a method based on saliency detection and attention convolutional neural network for OD detection. Firstly, the wavelet transform based saliency detection method is used to detect the OD candidate regions to the maximum extent such that the intensity, edge and texture features of the fundus images are all considered into the OD detection process. Then, the attention mechanism that can emphasize the representation of OD region is combined into the dense network. Finally, it is determined whether the detected candidate regions are OD region or non-OD region. The proposed method is implemented on DIARETDB0, DIARETDB1 and MESSIDOR datasets, the experimental results of which demonstrate its superiority and robustness.

This paper investigates the performance of an overloaded multiple-input multiple-output (MIMO) - orthogonal frequency division multiplexing (OFDM) system with and without antenna selection. In the overloaded MIMO-OFDM system, even if only a small amount of feedback is available, performance can be improved by selecting the transmit antennas. Thus, this paper compares the performance of an overloaded MIMO system with and without antenna selection under different code rates. It is shown that the performance of the MIMO-OFDM system for six signal streams with QPSK modulation is about 2.0dB better than that for three signal streams with 16QAM modulation while it is about 5.0dB better than that of the MIMO-OFDM system for two signal streams with 64QAM modulation at a bit error rate (BER) of 10-3. However, it is also shown that the performance of the overloaded MIMO system is worse if the code rate of the repetition code increases.

This paper proposes performance improvement schemes for non-coherent multiple-input multiple-output (MIMO) communication systems employing per transmit antenna differential mapping (PADM). PADM is one form of differential space-time coding (DSTC), which generates an independent differentially encoded sequence for each of the multiple transmit antennas by means of space-time coding and mapping. The features of the proposed schemes are as follows: 1) it employs an asymmetric space-time mapping instead of the conventional symmetric space-time mapping in order to lower the required signal to noise power ratio (SNR) for maintaining the bit error rate (BER) performance; 2) it employs an analytically derived branch metric criterion based on channel prediction for per-survivor processing (PSP) in order to track fast time-varying channels. Finally, computer simulation results confirm that the proposed schemes improve the required SNR by around 1dB and can track at the maximum Doppler frequency normalized by symbol rate of 5%.

Non-orthogonal multiple access (NOMA) enables multiple mobile devices to share the same frequency band. In a conventional NOMA scheme, the receiver of a far user detects its desired signal without canceling the signal for a near user. However, the signal for the near user acts as interference and degrades the accuracy of likelihood values for the far user. In this paper, a joint maximum likelihood detection scheme for the far user of the NOMA downlink is proposed. The proposed scheme takes the interference signal into account in calculating the likelihood values. Numerical results obtained through computer simulation show that the proposed scheme improves the performance by from 0.2dB to 3.1dB for power allocation coefficients of 0.2 to 0.4 at a bit error rate (BER) of 10-2 relative to the conventional scheme.

This paper proposes novel simplified maximum likelihood detection for XOR physical layer network coding (XOR-PNC) in bi-directional wireless relay systems with Quaternary phase shift keying (QPSK). The proposed detection applies unitary precoding to achieve superior performance without computationally prohibitive exhaustive search. The performance of the XOR employing the proposed simplified MLD with the precoding is analyzed in relay systems with orthogonal frequency division multiplexing (OFDM). The performance of the XOR-PNC with the proposed techniques is also evaluated by computer simulation. The XOR-PNC with the proposed techniques achieves about 7dB better performance than the amplify-and-forward physical layer network coding in the 5-path fading channel at BER=10-4. It is also shown that the XOR-PNC with the proposed techniques achieves better performance than that without precoding.

This letter presents a technique to reduce the complexity of the soft-output multiple-input multiple-output symbol detection based on Dijkstra's algorithm. By observing that the greedy behavior of Dijkstra's algorithm can entail unnecessary tree-visits for the symbol detection, this letter proposes a technique to evict non-promising candidates early from the search space. The early eviction technique utilizes layer information to determine if a candidate is promising, which is simple but effective. When the SNR is 30dB for 6×6 64-QAM systems, the average number of tree-visits in the proposed method is reduced by 72.1% in comparison to that in the conventional Dijkstra's algorithm-based symbol detection without the early eviction.

This letter proposes a low-complexity soft-detection algorithm for modified dual-carrier modulation (MDCM) in WiMedia ultra-wideband (UWB) systems. In order to reduce the complexity of soft-output maximum-likelihood detection (soft-MLD), which gives the optimal performance for MDCM symbols, the proposed algorithm utilizes the following three methods: real/imaginary separation, multiplierless distance calculation, and candidate set reduction. Through these methods, the proposed algorithm reduces the complexity of soft-MLD by 97%, while preventing the deterioration of its optimality. The performance of the proposed algorithm is demonstrated by simulations of 640–1024 Mbps transmission modes of the latest Release 1.5 standard of the WiMedia UWB.

In this letter, we focus on detecting a random primary user (PU) network for cognitive radio systems in a cooperative manner by using maximum likelihood (ML) detection. Different from traditional PU network models, the random PU network model in this letter considers the randomness in the PU network topology, and so is better suited for describing the infrastructure-less PU network such as an ad hoc network. Since the joint pdf required for the ML detection is hard to obtain in a closed form, we derive approximate ones from the Gaussian approximation. The performance of the proposed algorithm is comparable to the optimal one.

This paper proposes non-coherent multiple-input multi-ple-output (MIMO) communication systems employing per transmit antenna differential mapping (PADM), which generates an independent differentially encoded sequence for each of the multiple transmit antennas by means of space-time coding and mapping. At a receiver, the proposed PADM employs adaptive maximum-likelihood detection (MLD). The features of PADM are as follows: 1) it has excellent tracking performance for fast time-varying fading channels, because it can detect transmitted data without needing channel state information (CSI); 2) it can be applied not only to transmit diversity (TD) but also to spatial multiplexing (SM). In this paper, we analyze the adaptive MLD based on pseudo matrix inversion and derive its metric for data detection. In order to satisfy requirements on multiple transmitted sequences for the adaptive MLD, this paper proposes a mapping rule for PADM. Next, this paper describes a receiver structure based on per-survivor processing (PSP), which can drastically reduce the complexity of adaptive MLD. Finally, computer simulations confirm that the proposed non-coherent MIMO communication systems employing PADM have excellent tracking capability for TD and SM on fast time-varying fading channels.

This paper proposes an efficient list extension algorithm for soft-output multiple-input-multiple-output (soft-MIMO) detection. This algorithm extends the list of candidate vectors based on the vector selected by initial detection, in order to solve the empty-set problem, while reducing the number of additional vectors. The additional vectors are obtained from multiple detection orders, from which high-quality soft-output can be generated. Furthermore, a method to reduce the complexity of the determination of the multiple detection orders is described. From simulation results for a 44 system with 16- and 64-quadrature amplitude modulations (QAM) and rate 1/2 and 5/6 duo-binary convolutional turbo code (CTC), the soft-MIMO detection to which the proposed list extension was applied showed a performance degradation of less than 0.5 dB at bit error rate (BER) of 10-5, compared to that of the soft-output maximum-likelihood detection (soft-MLD) for all code rate and modulation pairs, while the complexity of the proposed list extension was approximately 38% and 17% of that of an existing algorithm with similar performance in a 44 system using 16- and 64-QAM, respectively.

An efficient pruning method is proposed for the infinity-norm sphere decoding based on Schnorr-Euchner enumeration in multiple-input multiple-output spatial multiplexing systems. The proposed method is based on the characteristics of the infinity norm, and utilizes the information of the layer at which the infinity-norm value is selected in order to decide unnecessary sub-trees that can be pruned without affecting error-rate performance. Compared to conventional pruning, the proposed pruning decreases the average number of tree-visits by up to 37.16% in 44 16-QAM systems and 33.75% in 66 64-QAM systems.

In order to realize multi-service in TDS-OFDM system, a novel multiplexing scheme based on space time block code is proposed along with the corresponding demultiplexing method with low complexity. Simulations show the presented scheme can not only achieve full diversity gain, but also effectively improve the system capacity.

In this paper, we propose a genetic algorithm (GA) based equalization approach for direct sequence ultra-wideband (DS-UWB) wireless communication systems, where the GA is combined with a RAKE receiver to combat the inter-symbol interference (ISI) due to the frequency selective nature of UWB channels for high data rate transmission. The proposed GA based equalizer outperforms significantly the RAKE and the RAKE-minimum mean square error (MMSE) receivers according to results obtained from intensive simulation work. The RAKE-GA receiver also provides bit-error-rate (BER) performance very close to that of the optimal RAKE-maximum likelihood detection (MLD) approach, while offering a much lower computational complexity.

In this paper, we propose a novel noncoherent maximum likelihood detection (NMLD) method for differential spatial multiplexing (SM) multiple-input multiple-output (MIMO) systems. Unlike the conventional maximum likelihood detection (MLD) method which needs the knowledge of channel state information (CSI) at the receiver, NMLD method has no need of CSI at either the transmitter or receiver. After repartitioning the observation block of multiple-symbol differential detection (MSDD) and following a decision feedback process, the decision metric of NMLD is derived by reforming that of MSDD. Since the maximum Doppler frequency and noise power are included in the derived decision metric, estimations of both maximum Doppler frequency and noise power are needed at the receiver for NMLD. A fast calculation algorithm (FCA) is applied to reduce the computational complexity of NMLD. The feasibility of the proposed NMLD is demonstrated by computer simulations in both slow and fast fading environments. Simulation results show that the proposed NMLD has good bit error rate (BER) performance, approaching that of the conventional coherent MLD with the extension of reference symbols interval. It is also proved that the BER performance is not sensitive to the estimation errors in maximum Doppler frequency and noise power.

An antenna-permutation (AP) scheme is described for channel-vector quantization (CVQ) in zero-forcing beamforming (ZFBF) multiuser multiple-input and multiple-output orthogonal frequency-division multiplexing systems with multiple receive antennas. Different sets of multiple channel sub-matrices are selected for different subcarriers and then quantized to multiple quantization vectors for finite rate feedback. Based on the quantization vectors, ZFBF provides a single stream or multiple streams to users while increasing frequency selectivity. Simulation results demonstrate that AP-CVQ with four-bit quantization that incorporates with pre-whitening maximum likelihood detection for two stream reception achieved better average packet error rates than minimum mean square error receive beamforming for single stream reception when the frequency selectivity was not severe.

This paper proposes an adaptive selection algorithm for the surviving symbol replica candidates (ASESS) based on the maximum reliability in maximum likelihood detection with QR decomposition and the M-algorithm (QRM-MLD) for Orthogonal Frequency Division Multiplexing (OFDM) multiple-input multiple-output (MIMO) multiplexing. In the proposed algorithm, symbol replica candidates newly-added at each stage are ranked for each surviving symbol replica from the previous stage using multiple quadrant detection. Then, branch metrics are calculated only for the minimum number of symbol replica candidates with a high level of reliability using an iterative loop based on symbol ranking results. Computer simulation results show that the computational complexity of the QRM-MLD employing the proposed ASESS algorithm is reduced to approximately 1/4 and 1/1200 compared to that of the original QRM-MLD and that of the conventional MLD with squared Euclidian distance calculations for all symbol replica candidates, respectively, assuming the identical achievable average packet error rate (PER) performance in 4-by-4 MIMO multiplexing with 16QAM data modulation. The results also show that 1-Gbps throughput is achieved at the average received signal energy per bit-to-noise power spectrum density ratio (Eb/N0) per receiver antenna of approximately 9 dB using the ASESS algorithm in QRM-MLD associated with 16QAM modulation and Turbo coding with the coding rate of 8/9 assuming a 100-MHz bandwidth for a 12-path Rayleigh fading channel (root mean square (r.m.s.) delay spread of 0.26 µs and maximum Doppler frequency of 20 Hz).

In multiple antenna systems that use spatial multiplexing to raise transmission rates, it is preferable to use maximum likelihood (ML) detection to exploit the full receive diversity and minimize the error probability. In this paper, we present two tree based approximate ML detectors that use new two ordering criteria in conjunction with efficient search strategies. Unlike conventional tree detectors, the new detectors closely approximate the error performance of the exact ML detector while achieving a dramatic reduction in complexity. Moreover, they ensure a fixed detection delay and high level of parallelization in the tree search.

A modified Schnorr-Euchner sphere decoding (SE-SD) algorithm to search for the receive minimum distance is presented. In the proposed algorithm, the visit to negative symmetric vectors of already spanned vectors is avoided by using a biased spanning, and the redundant processes to visit the all-zero vector are also eliminated. A numerical experiment shows that the modified SE-SD algorithm is much more efficient than the conventional algorithm in terms of average computational complexity.

This letter deals with computationally efficient maximum-likelihood (ML) detection for the quasi-orthogonal space-time block code (QOSTBC) with four transmit antennas. The proposed ML detector uses a permutation based real-valued equivalent channel matrix representation. As a result, the complexity of ML detection problem is moderated from O(2|A|2) to O(4|A|), where |A| is modulation order. Numerical results show that the proposed ML detector provides ML performance and achieves greatly high computational savings.