Active reconfigurable intelligent surface (RIS) is deemed a prospective candidate to compensate the double fading attenuation caused by the passive RIS, where each element can reflect and amplify the received signals through its low power integrating amplifiers. This paper investigates the physical layer security (PLS) for a non-orthogonal multiple access (NOMA) system through a deployed active RIS to defend multiple eavesdroppers (Eves), where the practical discrete RIS phase shift designs are taken into account. To characterize the secrecy performance, analytical expressions of secrecy outage probability (SOP) and effective secrecy throughput (EST) for an active RIS assisted NOMA (RIS-NOMA) system are derived based on heuristic approximations, which is in consideration of two scenarios with and without direct links. Furthermore, secrecy diversity orders are attained based on theoretical results, of which the convergence rates and gaps between the discrete and continuous phase shifting are further evaluated. The results reveal that a 4-bit quantization can achieve the secrecy diversity order of continuous phase shifts. Numerical results are furnished to corroborate the analyses, and illustrate that the security performance for active RIS-NOMA outperforms the passive RIS-NOMA and conventional cooperation communications under the same total power consumption. The impacts of phase quantization bit, amplification factor and the number of Eves as well as reflective elements on security performance are also substantiated by simulations.

The sixth-generation (6G) network is considered a promising enabler of the Internet of Things (IoT), with potential applications spanning from terrestrial to non-terrestrial terminals. In this paper, a novel orthogonal time frequency space (OTFS)-based pattern division multiple access (PDMA) scheme, shortened as OTFS-PDMA, is proposed to meet the low-latency, high-reliability, and massive connection requirements of 6G networks in high-mobility scenarios. A combined detection approach is proposed for the OTFS-PDMA scheme based on the expectation propagation algorithm (EPA). To mitigate the detrimental effect of base station antenna correlation, we design a vector EPA (V-EPA) receiver by combining different receive antennas at each delay-Doppler domain resource element. A pattern-aware serial mechanism is proposed to facilitate the convergence of the proposed EPA and V-EPA receivers by exploiting theconvergence-amenableproperty of the PDMA scheme. An iterative detection and decoding (IDD) structure with parallel interference cancellation (PIC) is integrated into the proposed receivers to further improve the system performance. Simulation results illustrate that the proposed OTFS-PDMA scheme with EPA-based receivers achieves significant performance gains over the conventional OTFS-OMA scheme. Moreover, the proposed V-EPA receiver provides a good performance-complexity trade-off, particularly in spatially correlated multiple-input multiple-output (MIMO) channels.

With the proliferation of emerging Internet of Things (IoT) applications, massive multiuser multiple-input–multiple-output (MU-MIMO) is a promising technology to support the massive connectivity requirement with limited spectral resources. The existing detection algorithms are mainly designed based on a centralized baseband processing architecture, which requires extremely high raw baseband data rates transferred between base-station antennas and the central processing unit (CPU). Decentralized baseband processing (DBP) architecture has recently been proposed to alleviate high interconnect data rates and chip input/output bandwidth bottlenecks. Since the information is not fully shared among each antenna cluster, conventional decentralized detectors suffer from significant performance loss, especially for systems with high overload ratios and/or spatially correlated channels. In this work, we first propose a decentralized groupwise detection paradigm for the star architecture by dividing users into multiple user groups, which can be effectively exploited by factor graph-based message passing algorithms, such as the expectation propagation (EP) algorithm. Then, an efficient message fusion rule is devised based on the product principle of the multivariate Gaussian probability density function at the CPU. To reduce the computational complexity, an approximate groupwise EP (AGW-EP) method is proposed by judiciously selecting reliable constellation vectors during the symbol belief calculation phase. In addition, we extend the proposed methods to the daisy-chain architecture, which requires constant interconnect data rates. Simulation results demonstrate that the proposed groupwise paradigm greatly enhances the performance of the conventional EP detector. Moreover, the proposed decentralized groupwise EP and AGW-EP detection schemes outperform their counterparts, particularly in correlated MIMO channels.

In this paper, we propose a joint signal detection algorithm under the framework of the expectation propagation (EP) algorithm for uplink massive multiuser multiple-input multiple-output (MIMO) systems with generalized spatial modulation (GSM). By projecting the discrete probability distribution into a multivariate complex Gaussian function, the symbol beliefs of the tridimensional GSM constellation are calculated via the iterative propagation of the mean vectors and covariance matrices. To reduce the computational complexity, an efficient separate signal detection called two-stage EP (TS-EP) algorithm is designed. In the first stage, the active transmit antenna indices are determined via the EP. Each vector-valued variable node (VN) in the factor graph is decomposed into multiple sub-VNs, and the invalid sub-VNs of the determined silent transmit antennas are pruned from the factor graph. In the second stage, since the modulation symbols are independent conditioned on the active transmit antennas, the symbols are independently detected by adopting the EP with univariate complex Gaussian approximations, and the number of probability calculations for each symbol belief is significantly reduced in the subsequent EP update. Simulation results illustrate that the proposed EP and TS-EP signal detection schemes outperform the recently proposed counterparts. Moreover, the proposed TS-EP algorithm strikes a desirable and flexible performance-complexity tradeoff.

Orthogonal frequency division multiplexing‐based pattern division multiple access (PDMA) is considered as a promising multiple access scheme for future wireless communication systems due to its high spectral efficiency and powerful ability to support massive users. In this study, it is shown that two pattern matrices with unequal diversity gain in the PDMA system have better convergence performance compared with the signature matrices in a traditional low‐density signature multiple access system by simulations and extrinsic information transfer (EXIT) chart analysis. For a low‐density parity check (LDPC)‐coded PDMA system, the EXIT characteristics between the front‐end multiple‐user detector (MUD) and the LDPC decoder may be mismatch, which usually leads to degraded performance when an iterative detection and decoding algorithm is used. To overcome this problem, a two‐stage iterative optimisation algorithm, which is easy to implement is proposed to find an optimal (near optimal) degree distribution pair for the LDPC code. Both EXIT chart analysis and simulation results demonstrate that the proposed algorithm exhibits further performance gain compared with regular (3,6) LDPC‐coded systems under both an additive white Gaussian noise channel and a Rayleigh fading channel.

In this paper, a unified framework of non-orthogonal multiple access (NOMA) networks is proposed, which can be applied to code-domain NOMA (CD-NOMA) and power-domain NOMA (PD-NOMA). Since the detection of NOMA users mainly depend on efficient successive interference cancellation (SIC) schemes, both imperfect SIC (ipSIC) and perfect SIC (pSIC) are taken into considered. To characterize the performance of this unified framework, the exact and asymptotic expressions of outage probabilities as well as delay-limited throughput for CD/PD-NOMA with ipSIC/pSIC are derived. Based on the asymptotic analysis, the diversity orders of CD/PD-NOMA are provided. It is confirmed that due to the impact of residual interference (RI), the outage probability of the n-th user with ipSIC for CD/PD-NOMA converges to an error floor in the high signal-to-noise ratio (SNR) region. Numerical simulations demonstrate that the outage behavior of CD-NOMA is superior to that of PD-NOMA.

Task scheduling is one of the most critical issues on cloud platform. The number of users is huge and data volume is tremendous. Requests of asset sharing and reuse become more and more imperative. Efficient task scheduling mechanism should meet users' requirements and improve the resource utilization, so as to enhance the overall performance of the cloud computing environment. In order to solve this problem, considering the new characteristics of cloud computing and original adaptive genetic algorithm(AGA), a new scheduling algorithm based on double-fitness adaptive algorithm-job spanning time and load balancing genetic algorithm(JLGA) is established. This strategy not only works out a tasks scheduling sequence with shorter job and average job makespan, but also satisfies inter-nodes load balancing. At the same time, this paper adopts greedy algorithm to initialize the population, brings in variance to describe the load intensive among nodes, weights multi-fitness function. We then compare the performance of JLGA with AGA through simulations. It proves the validity of the scheduling algorithm and the effectiveness of the optimization method.

In this paper, a novel remapping design for multiway relay system with multi-user (MU) is presented. Every user exchanges information with its partners via the relay. The two communication terminals have different modulation schemes according to their individual channel quality.We term this system an adaptive modulation asymmetric multi-way relaying networks, in which signal space alignment for network coding (SSA-NC) and interference nulling beamforming are exploited. For the case of the asymmetric scenario, we design a remapping function in symbol-level at the relay and the corresponding decoding rules at the user side. Monte Carlo simulations demonstrate that the proposed scheme can achieve significant gain.

An iterative detection and decoding (IDD) scheme based on component-level soft cancellation (CLSC) and linear minimum mean-squared error (LMMSE) filtering for turbo coded multiple input multiple output (MIMO) multiplexing systems is proposed in this work. By exploiting the independence between the In-phase and Quadrature-phase branch, more accurate soft interference cancellation is realized. Extrinsic information transfer (EXIT) characteristics of the IDD system show that the proposed scheme exhibit faster convergence speed than the conventional one. Numerical results validate that the CLSC-LMMSE based detection algorithm achieves noticeable bit error rate (BER) performance over symbol-level soft cancelation (SLSC) based one, with only marginal complexity increase.

In this work, an allele gene adaptive mutation (AGAM) and a schemata crossover (SC) operators are designed to improve the performance of the conventional genetic algorithm (GA) and applied to the code design. Specifically, the proposed AGAM exploits both global and local information of the population to maintain an appropriate level of diversity throughout the search process. The SC utilizes high-performance schemata to enhance the traditional crossover operation. The combination of the AGAM and SC achieves both goals of maintaining population diversity and simultaneously sustaining the convergence capability of the GA. As a result, the SC and AGAM based genetic algorithm alleviates the inherent premature convergence of the GA, thus significantly increasing the chance of locating the global optimal solution. The application of the proposed allele based adaptive genetic algorithm (AGAGA) to the universal mobile telecommunications system (UMTS) time-division duplex (TDD) mode leads to significant performance gains on autocorrelation (6.1 dB) and cross-correlation properties (2.0 dB) over those of the current standard.

In this work, we propose a rotation-based transformation method and apply it to the QRD-M detector for MIMO systems with the commonly used square quadrature amplitude modulation (S-QAM) or amplitude and phase-shift keying (APSK). The QRD-M detector based on proposed rotation transformation principle method achieves 50% computation reduction for MIMO systems with 4-QAM compared with the original QRDM algorithm (25% for those with 16-QAM) without sacrificing any performance. The proposed rotated QRD-M method achieves performance close to the maximum-likelihood (ML) detector with computational complexity lower than the linear detector for MIMO systems with 4-QAM. The underlying principle of the proposed rotation-based transformation method can be extended to S-QAM (or APSK) modulated MIMO systems with employing sphere decoding (SD), list sphere decoding (LSD), list sequential sphere decoder (LISS) (or other quasi-ML methods), and the full ML based methods in a straightforward manner.

The merit factor (MF) introduced by Golay has long been accepted as the standard criterion to evaluate and design binary sequences with good anti-multipath property in sonar, radar, and communication systems for its theoretical tightness and practical simplicity. In this paper, we first show that the MF is a biased anti-multipath performance evaluation metric in theory and, more importantly, is not a pertinent sequence design criterion in practice for most binary sequences of practical interest. Then we propose theweightedmeritfactor(WMF) based on a non-uniform weighting of the out-of-phase aperiodic autocorrelation function (ACF) that provides accurate measurement of self-generated interference for the constant amplitude complex-valued sequences and the nonconstant modulus ones. Based on the WMF, a list of "bad" (of low MFs) binary sequences (lengths 33-95) with better anti-multipath performance than the "best" (known) ones have been designed to verify its greater pertinence over the MF as a sequence design criterion for sonar, radar, and communication systems. Moreover, we extend the weighted correlation model of the WMF to the code-division multiple-access (CDMA) systems and propose theweightedcross-correlationfactor(WCF) to evaluate the sequence set's multiple-access interference (MAI) rejection property in the context of multipath propagation. Theoretical analysis corroborated by simulations confirms that the WCF provides greater practical pertinence and analytical tractability over the current standard criterion.

The merit factor (MF) introduced by Golay has long been accepted as the standard criterion to evaluate the binary sequence's anti-multipath property in sonar, radar, and communication systems for its simplicity and seemly infallibility. First we present two binary sequence pairs (of lengths 32 and 64) of identical MFs with great discrepancies between the respective binary sequence pairs' uncoded symbol-error rate (SER) performance and theoretical analysis (based on the MF) to shed new light on the hitherto unnoticed determining factor of the sequence's anti-multipath property. We then propose the weighted merit factor (WMF) based on a non-uniform weighting of the out-of-phase aperiodic autocorrelation function (ACF) which leads to better matches between the cited sequence pairs' analytical and experimental results. Ensuing theoretical analysis demonstrates that the WMF provides optimal measurement of self-generated interference for the constant amplitude complex-valued sequences and the nonconstant modulus ones. The MF is shown to be a biased metric for the binary sequences when the multipath delay spread exceeds one chip period. We conjecture that this conclusion continues to hold true for the constant amplitude complex-valued sequences.