Reconfigurable Intelligent Surface (RIS) is a highly promising technology that can enhance the performance of Mobile Edge Computing (MEC) networks. Various Deep Reinforcement Learning (DRL)-based methods have been proposed for power and phase-shift matrix allocation in RIS-assisted communication systems, applicable to environments with hardware defects and imperfect Channel State Information (CSI). However, existing methods primarily focus on resource allocation at the physical layer and fail to fully address cross-layer issues related to video transmission. Therefore, this paper proposes a cross-layer resource allocation method for RIS-assisted communication systems in video transmission, changing the reward function from maximize computation rate to jointly optimize computation rate and average PSNR Ratio (PSNR)

With the advancement of mobile communication technology, there has been a marked increase in the demand for personalized and ubiquitous Internet of Things (IoT) services, raising the expectations for network Quality of Service (QoS) and Quality of Experience (QoE). Existing popularity-prediction-based content caching policies improve QoS and QoE by precaching contents at the network edge, but jointly optimizing multiple network metrics remains a challenge. To address this challenge, we propose a many-objective optimization-based popularity prediction for cooperative caching (MaOPPC-Caching) framework for cloud–edge–end collaborative IoT networks. This framework simultaneously optimizes prediction accuracy, delay, offloaded traffic, and load balance. We integrate three prediction algorithms to forecast content popularity and present a horizontal and vertical collaborative caching decision strategy to generate caching forms based on the predicted results. Then, the many-objective evolutionary algorithm (MaOEA) is employed to optimize the combined proportions to take full advantage of hidden preferences and popularity characteristics of both users and items. To promote the convergence of the framework, we present a knowledge mining-based MaOEA (KMaOEA) to incorporate knowledge mining into the optimization process. Simulation results show that the proposed MaOPPC-Caching framework outperforms existing prediction algorithms in terms of four evaluation indicators. Furthermore, KMaOEA shows a significant advantage over NSGA-III in load balance, as indicated by a Mann–Whitney rank sum test with a$p$-value of 0.040.

To satisfy the differentiated service requirements of delay-sensitive and computing-intensive tasks, it is urgent to efficiently allocate limited network resources to improve content distribution in cloud-edge environments. In this paper, we proposes a task partition-based intelligent offloading scheme to optimize resource allocation in cache-assisted cloud-edge cooperation environments. Specifically, we formulate the task partition-based optimal computation offloading problem as a latency minimization model in the cache-aided cloud-edge collaboration system. A new deep reinforcement learning (DRL) algorithm is designed to make optimal subtask offloading and resource allocation decisions based on current network state information, improving resource utilization and network delay. Simulation results demonstrate that the proposed model achieves lower-latency content delivery than the existing popular models in cache-enabled cloud-edge cooperation networks, and fast converges.

To satisfy differentiated service requirements of delay-sensitive and computing-intensive tasks in satellite communication networks, we propose a cache-assisted low-latency content distribution scheme in multi-cell multi-carrier nonorthogonal multiple access (MCMC-NOMA)-based satellite-edge-terminal cooperation environments. In the paper, a delay minimization problem is formulated to achieve optimal content distribution by jointly optimizing the allocation of subchannels and transmit power, which is decomposed and solved in each slot by using many-to-one matching and successive convex approximation, respectively. Simulation results show that the proposed model significantly improve network latency and content distribution in comparison to its existing counterparts in cloud-edge-terminal cooperation networks.

Polar coding subject to memoryless impulse noise described by a Gaussian mixture model is investigated. In contrast with existing approaches resorting to latency-laced interleaving, this paper tackles statistical dependence between in-phase and quadrature components of impulse noise, attributable to employing higher order modulation schemes, with meticulous revision in successive cancellation decoding. Furthermore, forfeiting using the statistical knowledge of impulse noise, a density evolution-based code construction method is proposed. Challenges of the aggravated complexity-ensued from addressing the aforementioned statistical dependence-are subsequently overcome by an approximation approach. The block error rate performance for the proposed framework is investigated by computer simulations and the experimental results exhibit the markedly performance gain over the conventional construction method under certain circumstances.

Aggregating a lot of subcarriers will generate high peak‐to‐average power ratio (PAPR) which makes the overall system performance degradation. Among the existing PAPR reduction methods for orthogonal frequency‐division multiplexing (OFDM)‐based systems, iterative clipping and filtering (ICF) may be easy to implement, but ICF may cause signal distortion, so that the system cannot approximate the processed signals to the original signals which degrades error rates at receivers. Here, the authors proposed a new method based on ICF with smoothed clipping signals, and find the optimised filter to achieve the minimum error vector magnitude and efficiently reduce PAPR. Owing to the lack of a wide range of continuous bandwidth, the Third Generation Partnership Project proposed carrier aggregation (CA) technology in LTE‐advanced systems. CA can aggregate many contiguous or non‐contiguous fragment spectrums for supporting larger bandwidth and higher peak data rate. Here, the authors also evaluate the developed PAPR reduction scheme for the use in CA scenarios. The efficacy of the proposed scheme is demonstrated in the simulation results.

In this paper, we provide comprehensive comparison for Interleave Division Multiple Access (IDMA) and Code Division Multiple Access (CDMA) with channel coding or not with Minimal Mean Square Error (MMSE) filter or not. The following three cases (1) uncoded (2) long code CDMA without MMSE filter (3) short code CDMA with MMSE filter are not found in the literatures. Although the other types of CDMA systems under-perform the IDMA system, the long code CDMA system with MMSE filter and scrambling is close to that of the IDMA system in BER performance. Thus IDMA is not significantly better than all CDMA systems.

In this paper, we discuss the procedures how to make Viterbi decoder faster. The implementation in Intel CPU with SSE4 parallel processing instruction sets and some other methods achieves the decoding speed 47.05 Mbps (0.64 Mbps originally). The DVB-T mode used in Taiwan needs 13.27 Mbps to achieve real-time reception, so our implementation of software Viterbi decoder takes only 28% CPU loading.

We consider multiuser MIMO CDMA systems where each user has multiple transmit antennas and different transmit antennas of the same user use the same spreading code. Because transmit antennas of the same user use the same spreading code, inter antenna interference would degrade the system performance. We propose a novel decision-window-based data detection (sequential detection) method to mitigate the inter antenna interference. We also modify the existing single-user single-antenna channel estimation algorithm for multiuser multiantenna systems. The simulation results show that, under the same channel estimation algorithm, the proposed sequential detection scheme with decision window of two symbols significantly outperforms the non-sequential one which is a special case of the proposed one when the decision window is of one symbol. It also outperforms the existing SIC-VBLAST, decorrelator-VBLAST, and MMSE-VBLAST schemes.

The problem of joint symbol synchronization and decoding of pulse position modulation (PPM) sequences in the deep-space photon-limited optical channel is considered. A new joint synchronizer and decoder for PPM on this channel is presented along with the design of codes having both good error control and synchronization properties for use with PPM signaling on this channel. The new approach presented in this paper provides a significant reduction in synchronizer/decoder complexity when compared to previous methods for joint synchronization and decoding.

In this paper, we propose the use of standard, verifiable, common approach Platform called The Flexible Wireless Sensor platform (FWSP) architecture which had following features remote internet enabler, Reconfiguration by parameter which improve precision, Dynamic addition of sensor nodes, and fault tolerance which increase the reliability, stability. The goals of the FWSP architecture are to establish: common controller-hardware(System on module), a common control program, common device drivers, a common managed objects base, and a common appearance to higher-level sensor network management. The proposed platform architecture offers flexibility, easy customization ,and seamless system integration. An Experiment has been established based on wireless communication channel. using wireless Lan ( IEEE802.11) [1] as primary communication channel on our prototype Sensor node , I2C /Smbus [2] device such as temperature sensors, and desire sensor information can be viewed, and Sensor parameter can be adjusted to meet demanding. Measurements about the development time , sensor reconfiguration and confirm the proposed framework feasibility and effectiveness.

Recently, Gao et al. proposed the expectation-maximization (EM) vector channel estimation for single-user direct-sequence code-division multiple-access (DS-CDMA) systems to estimate the correlated fading channel coefficients of the paths of a user. They also used one D-lag decision-feedback maximum a posteriori (MAP) detector to detect the information bits. A straightforward extension (noniterative) to multiuser synchronous CDMA cases, i.e., adding the parallel interference cancellation (PIC) multiuser detector into their scheme, results in poor performance. Therefore, we propose an iterative scheme which combines vector channel estimation, decision-feedback MAP detection, and PIC. The partial PIC is applied in the sequence hypothesis stage of MAP in each iteration before the final MAP decision. The proposed scheme has twice the decision delay of the previous scheme for single-user cases. The performance of the proposed system in the time-selective, correlated multipath fading channel environment is investigated. Simulation results show that the proposed scheme significantly outperforms the noniterative scheme. Simulation results also show that the proposed scheme performs better than its scalar channel-estimation version.

Recently, it has been shown that the received signal in the OFDM systems can be viewed as the synchronous code-division multiple access (SCDMA) signal in receiver after some mathematical manipulation, and the ICI term in the OFDM system is equivalent to the multiple access interference (MAI) term in synchronous CDMA system. They proposed a successive interference cancellation multicarrier detector and it performs better than conventional single-carrier detection schemes in time-varying multiple channel (Doppler/spl ne/0). To further improve the performance of OFDM systems in the presence of ICI, we propose to use a soft-in soft-out (SISO) multicarrier detector and a SISO convolutional decoder in an iterative (turbo) way. The simulation results show that the first iteration of the proposed scheme demonstrates 2-3 dB gain compared to the previous multicarrier detection schemes.

Recently, a training-based vector channel estimation scheme has been proposed for single-user CDMA systems with aperiodic spreading codes. In this paper, we extend it to the reverse link of multiuser MIMO CDMA system. We also use the generalized MMSE multiuser detector to suppress multiuser interference so then we can get good initial vector channel estimates for each user. In the data transmission period, we combine the generalized MMSE multiuser detector, the maximum likelihood (ML) MIMO detector, and vector channel prediction of next channel vectors. The simulation results show that the vector channel estimation outperforms scalar channel estimation in multiuser MIMO CDMA systems.

The dual-bus optical network with nonregenerative stations has become popular. In general, the nonregenerative station implementation is better than the regenerative station implementation in media access control delay, cost, and susceptibility of station failures, etc. In this paper, two novel cycle-based protocols, named as synchronous wavelength sharing protocol (SWSP) and synchronous wavelength reusing/sharing protocol (SWRP), are proposed for nonregenerative wavelength-division-multiplexing dual-bus networks. The simulation results show that the network throughput and delay of SWRP are better than those of SWSP, when the numbers of wavelengths and tunable receivers are both limited, and/or the network traffic load is heavy.

The full parallel multistage detection for multiple-input multiple-output systems has less processing delay and better performance than the vertical Bell Laboratories layered space-time detection scheme. However, due to the disadvantage of full parallel interference cancellation, its performance degrades when the received power of the substreams at one receiving antenna is unbalanced and/or when the system is heavily loaded. Therefore, we introduce adaptive partial weighting coefficients into the parallel multistage detection. The weighting coefficients are evaluated using the average decision correct probabilities in the previous stage. The simulation results show that the uncoded error probability of the proposed method is lower than that of the recently proposed full parallel multistage detection scheme with perfect or imperfect channel estimation.

In a multicarrier direct-sequence code-division multiple access (MC DS CDMA) system, different fading channels for different user and/or different carrier are correlated in general, thus a vector channel model is more appropriate than the disjoint scalar channel models For multiuser MC DS CDMA systems, we propose (1) a generalized vector autoregressive model which accounts for correlation between different user/carrier fading channels, (2) the use of a blind, two-phased algorithm to obtain the proposed model's parameters, and (3) a receiver structure that consists of a generalized decorrelator followed by a maximal-ratio combining (MRC) of uncorrelated carrier channel outputs of each user. The estimated fading coefficients provides the necessary quantities to MRC. The computer simulation results have shown that the proposed scheme has a close performance to the case when the channel is perfectly known, and outperforms separate scalar channel estimation case.

The dual-bus optical network with non-regenerative stations has become popular. In general, the non-regenerative implementation is better than the generative implementation. In this paper, two protocols are proposed to improve the performance of this network. These two protocols are "synchronous wavelength sharing protocol (SWSP)" and "synchronous wavelength reusing/sharing protocol (SWRP)". The simulation results show that the network throughput is better than those of SWSP in the situation of a limited number of wavelengths, tunable receivers and heavy traffic loading.

We propose an optically (though not all-optically) decodable error-correction code. The structure of the proposed code is defined in the Fourier spectrum domain. The Fourier spectrum of the codewords has zeros. Thus, we can view any signal appearing in these spectrum zeros as the "syndrome", since the codewords have no energy in these spectrum zeros. The optical technique of the Fourier transform is used for fast decoding speed. The proposed code is nonlinear and of length eight. This code has a total of eight codewords (so the code rate is (log/sub 2/8)/8=3/8) and can correct 1.75 consecutive bit errors on average.

In this work, we will consider the problem of joint symbol synchronization and decoding of pulse position modulation (PPM) sequences in the deep-space photon-limited optical channel, where joint synchronization and decoding is significantly superior to separate synchronization and decoding. We also consider the design of codes having both good error control and synchronization properties for use with PPM signaling on this channel. While schemes for joint synchronization and decoding on this channel have been previously investigated, the complexity of these schemes has been prohibitive. In addition, their optimality with respect to computational complexity depends on the assumption that symbols are statistically independent and hence uncoded. We propose a two-stage joint synchronizer and decoder that achieve a selected performance requirement while reducing the complexity of joint synchronizer and decoder. The complexity is reduced by terminating synchronization once this error probability requirement is achieved, at which point the synchronizer/decoder functions only as a decoder on the remaining symbols in the received sequences. Therefore, the proposed scheme has practical complexity in the deep-space photon-limited optical channel, which may be used in the future deep-space missions.

We propose a fuzzy PIC multiuser detection/vector channel prediction scheme in Rayleigh fading channels. The vector channel prediction is based on the first-order auto-regressive model and the expectation-maximization algorithm. The signal-to-interference ratio and signal-to-noise ratio are estimated from the vector channel model's parameters, and we adapt the weight of each interference cancellation path via fuzzy inference mechanism. The proposed fuzzy PIC and vector channel prediction cooperate in a way that fuzzy PIC' some input parameters come from the channel predictor and fuzzy PIC makes the channel predictor more accurate at the next stage. Computing weights via the fuzzy adaptive method adds insignificant complexity because it involves only table lookup. The overall complexity is still linear in the number of users. The simulation results show that the proposed fuzzy PIC/vector channel prediction scheme performs better than previous improved PIC schemes in Rayleigh fading channels.

The use of sets of multiple spreading sequences per user in multicarrier code-division multiple-access (CDMA) is investigated. Each user is assumed to have a distinct set of spreading sequences, with a different spreading sequence for each carrier in each user's set. We show that when these sets of sequences are chosen to be the mutually orthogonal (MO) complementary sets of sequences, multiple-access interference is minimal on a nonfading channel. As a result of the autocorrelation sidelobe cancellation properties of the MO complementary sequences, it is possible to pack symbols more closely together on the nonfading channel, resulting in a higher data rate than in multicarrier CDMA using the same spreading sequence for each carrier. The resulting communication system scheme results in an easily parallelized receiver architecture that may be useful in nonfading coherent channels, such as the optical fiber channel or the Rician channel with a strong line-of-sight component. On the Rayleigh fading channel, the performance of the system is identical to that of multicarrier CDMA employing a single spreading sequence per user, with only a minimal increase in receiver complexity.