Effective Capacity of URLLC over Parallel Fading Channels with Imperfect Channel State Information

This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state information(CSI).Based on reasonable assumptions and approximations,we derive the effective capacity as a function of the pilot length,decoding error probability,transmit power and the sub-channel number.Then we reveal significant impact of the above parameters on the effective capacity.A closed-form lower bound of the effective capacity is derived and an alternating optimization based algorithm is proposed to find the optimal pilot length and decoding error probability.Simulation results validate our theoretical analysis and show that the closedform lower bound is very tight.In addition,through the simulations of the optimized effective capacity,insights for pilot length and decoding error probability optimization are provided to evaluate the optimal parameters in realistic systems.

Preparation of semisolid A356 alloy slurry with larger capacity cast by serpentine channel

The integral microstructure of semisolid A356 alloy slurry with larger capacity cast by serpentine channel was studied and the influence of cooling ability of serpentine channel on the microstructure was investigated. The results indicate that ideal slurry with larger capacity can be prepared through serpentine channel with good cooling ability. When the serpentine channel was continuously cooled, both the longitudinal and the radial microstructure of the slurry was composed of granular primary phase and the integral microstructure uniformity of the slurry was good. However, uncooled serpentine channel can only produce larger slurry with fine grains in positions adjacent to its centre and with a large number of dendrites in positions close to its edge, thus, the radial microstructure of larger slurry is nonuniform. The pouring temperature is set up to 680 °C and the solid shell inside the channel can be avoided at this pouring temperature.

A Correlation-Based Stochastic Model for Massive MIMO Channel

In this paper,the channel impulse response matrix(CIRM)can be expressed as a sum of couplings between the steering vectors at the base station(BS)and the eigenbases at the mobile station(MS).Nakagami distribution was used to describe the fading of the coupling between the steering vectors and the eigenbases.Extensive measurements were carried out to evaluate the performance of this proposed model.Furthermore,the physical implications of this model were illustrated and the capacities are analyzed.In addition,the azimuthal power spectrum(APS)of several models was analyzed.Finally,the channel hardening effect was simulated and discussed.Results showed that the proposed model provides a better fit to the measured results than the other CBSM,i.e.,Weichselberger model.Moreover,the proposed model can provide better tradeoff between accuracy and complexity in channel synthesis.This CIRM model can be used for massive MIMO design in the future communication system design.

Achievability of Chong-Motani-Garg relay channel capacity bounds using forward decoding

To reduce decoding delay of a communication scheme which is backward-decoding-based and achievable Chong Motani-Garg capacity bounds, a novel forward-sliding-window decoding-based communication scheme is proposed. In this scheme, if w = （w1, w2） is the message to be sent in block b, the relay will decode message w1 and generate a new message z at the end of block b, and the receiver will decode message w1 at the end of block b ＋ 1 and decode message z and w2 at the end of block b ＋ 2. Analysis results show that this new communication scheme can achieve the same Chong-Motani-Garg bounds and the decoding delay is only two blocks which is much shorter than that of backward decoding. Therefore, Chong-Motani-Garg bounds can be achieved by a forward decoding-based communication scheme with short decoding delay.

Assessment of the Recent Hydromorphological Features of Nokoue Lake and Its Channels (South-East Benin)

Based on 2022 and 2023 hydrometric data and satellite images (Sentinel 2022, SPOT 2010), this study aims to present the Nokoué Lake and its channels’ re-cent hydromorphological characteristics. Integrating flow, tributary morphology, and topography data determined specific power values along the axes studied. The values obtained range from 2.69 to 12.92 W/m2 for Ouémé River and 2.46 to 10.99 W/m2 for Sô River. The resulting water erosion on banks and bottoms is of linear, areolar, or gully and claw types. Lake bathymetry varies from -0.5 to -2.6 m (low flow period) and -1 to -4 m;in the Ouémé, Sô, and Totchè rivers, it varies from -5 m to -7 m, reaching -10 m at the Cotonou channel entrance (flood period). Bathymetric profiles reveal varied “U”, “V” and “Intermediate” bottom morphologies, influenced by erosion/sedimentation processes and human activities. The flow facies identified are lentic in the northern tributaries and lotic in the Cotonou and Totchè canals. Spatial analysis identified nine (09) thematic classes. In 2022, the surface area of the water body has increased from 274 km2 at low water to 280 km2 at high water, whereas in 2010 (a recent year of exceptional flooding), the surface area was 270 km2 at low water and 277 km2 at high water. Significant changes in land use are observed between 2010 and 2022. The floodplain area decreased slightly, from 421 km2 in 2010 (year of exceptional flooding) to 419 km2 in 2022. The evolution of land use shows a progressive expansion of the urban environment to the detriment of the natural environment. In the medium to long term, this trend could threaten the hydromorphological balance and even the existence of this important lagoon ecosystem.

Channel capacity and digital modulation schemes in correlated Weibull fading channels with nonidentical statistics

The novel closed-form expressions for the average channel capacity of dual selection diversity is presented, as well as, the bit-error rate （BER） of several coherent and noncoherent digital modulation schemes in the correlated Weibull fading channels with nonidentical statisticS. The results are expressed in terms of Meijer＇s Gfunction, which can be easily evaluated numerically. The simulation results are presented to validate the proposed theoretical analysis and to examine the effects of the fading severity on the concerned quantities.

Capacity Maximization Based Power Loading Analysis for Digital Channelized Satcom Systems

For digital channelized frequency division multiple access based satellite communication(SATCOM) systems,it is a challenging but critical issue to improve the transponder power and spectrum efficiency simultaneously under limited and non-linear high-power amplifier conditions.In this paper,different from the traditional link supportability designs aiming at minimizing the total transponder output power,a maximal sum Shannon capacity optimization objective is firstly raised subject to link supportability constraints.Furthermore,an efficient multilevel optimization(MO) algorithm is proposed to solve the considered optimization problem in the case of single link for each terminal.Moreover,in the case of multiple links for one terminal,an improved MO algorithm involving Golden section and discrete gradient searching procedures is proposed to optimize power allocation over all links.Finally,several numerical results are provided to demonstrate the effectiveness of our proposals.Comparison results show that,by the MO algorithm,not only all links' supportability can be guaranteed but also a larger sum capacity can be achieved with lower complexity.

Investigations into the Effect of Spatial Correlation on Channel Estimation and Capacity of Multiple Input Multiple Output System

The paper reports on investigations into the effect of spatial correlation on channel estimation and capacity of a multiple input multiple output (MIMO) wireless communication system. Least square (LS), scaled least square (SLS) and minimum mean square error (MMSE) methods are considered for estimating channel properties of a MIMO system using training sequences. The undertaken mathematical analysis reveals that the accuracy of the scaled least square (SLS) and minimum mean square error (MMSE) channel estimation methods are determined by the sum of eigenvalues of the channel correlation matrix. It is shown that for a fixed transmitted power to noise ratio (TPNR) assumed in the training mode, a higher spatial correlation has a positive effect on the performance of SLS and MMSE estimation methods. The effect of accuracy of the estimated Channel State Information (CSI) on MIMO system capacity is illustrated by computer simulations for an uplink case in which only the mobile station (MS) transmitter is surrounded by scattering objects.

Quantitative description of characteristics of high-capacity channels in unconsolidated sandstone reservoirs using in situ production data

Quantitative description of the high-capacity channels in unconsolidated sandstone reservoirs, into which water was injected to improve oil recovery, is a hot topic in the field of reservoir development. This paper presents a novel approach to describing quantitatively the characteristics of connected macropores in unconsolidated sandstone reservoirs using in situ production data. Based on physical simulation for formation mechanisms of high capacity channels and interwell tracer test data, a mathematical model was established to describe high-capacity channels by grey correlation theory, flow mechanism of fluid in porous media and reservoir engineering, and a program was developed to describe quantitatively the channel characteristics. The predicted results were consistent with field monitoring data （80%）, so this model could be economically and effectively used to identify high-capacity channels.

Channel capacity of multiple-input multiple-output systems with transmit and receive correlation

In order to investigate the impact of channel model parameters on the channel capacity of a multipleinput multiple-output （MIMO） system, a novel method is proposed to explore the channel capacity under Rayleigh fiat fading with correlated transmit and receive antennas. The optimal transmitting direction which can achieve maximum channel capacity is derived using random matrices theory. In addition, the closed-form expression for the channel capacity of MIMO systems is given by utilizing the properties of Wishart distribution when SNR is high. Computer simulation results show that the channel capacity is maximized when the antenna spacing increases to a certain point, and furthermore, the larger the scattering angle is, the more quickly the channel capacity converges to its maximum. At high SNR （〉12 dB）, the estimation of capacity is close to its true wlue. And, when the same array configuration is adopted both at the transmitter and the receiver, the UCA yields higher channel capacity than ULA.

Impact of channel estimation error on channel capacity of multiple input multiple output system

In order to investigate the impact of channel estimation error on channel capacity of multiple input multiple output (MIMO) system, a novel method is proposed to explore the channel capacity in correlated Rayleigh fading environment. A system model is constructed based on the channel estimation error at receiver side. Using the properties of Wishart distribution, the lower bound of the channel capacity is derived when the MIMO channel is of full rank. Then a method is proposed to select the optimum set of transmit antennas based on the lower bound of the mean channel capacity. The novel method can be easily implemented with low computational complexity. The simulation results show that the channel capacity of MIMO system is sensitive to channel estimation error, and is maximized when the signal-to-noise ratio increases to a certain point. Proper selection of transmit antennas can increase the channel capacity of MIMO system by about 1 bit/s in a flat fading environment with deficient rank of channel matrix.

Quantum speed-up capacity in different types of quantum channels for two-qubit open systems

A potential acceleration of a quantum open system is of fundamental interest in quantum computation, quantum communication, and quantum metrology. In this paper, we investigate the ＂quantum speed-up capacity＂ which reveals the potential ability of a quantum system to be accelerated. We explore the evolutions of the speed-up capacity in different quantum channels for two-qubit states. We find that although the dynamics of the capacity is varying in different kinds of channels, it is positive in most situations which are considered in the context except one case in the amplitude-damping channel. We give the reasons for the different features of the dynamics. Anyway, the speed-up capacity can be improved by the memory effect. We find two ways which may be used to control the capacity in an experiment： selecting an appropriate coefficient of an initial state or changing the memory degree of environments.

Statistical-mechanical analysis of multiuser channel capacity with imperfect channel state information

In this paper, the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analysed through a statistical-mechanical approach. Replica analyses focus on analytically studying how the minimum mean square error （MMSE） channel estimation error appears in a multiuser channel capacity formula. And the relevant mathematical expressions are derived. At the same time, numerical simulation results are demonstrated to validate the Replica analyses. The simulation results show how the system parameters, such as channel estimation error, system load and signal-to-noise ratio, affect the channel capacity.

Performance analysis on channel capacity in cooperative MIMO system

Recent years, cooperative technology has taken a lot of attention since it can improve the bit error rate （BER） and lower the transmit power in radio mobile networks, especially when the direct channel between the source and the destination is poor. Cooperative multiple input multiple output （Co-lVlIMO） is a kind of MI- MO technique, where the multiple inputs and outputs are formed via cooperation. The capacity of Co-MIMO system over wireless channel has been investigated a lot, however few papers pay attention to the locations of the channel that may affect the probability distributions of the variable and the effect of antenna spatial correlation. The results can be achieved by choosing sub-channels that is not related to other sub-channels. This paper focu- ses on this problem. The simulation results show that once we search the partner we should consider trade offs cooperation get optimum system performance. It further investigates that cooperation between different terminals can reduce antenna spatial correlation, thereby increase the capacity and throughput of the system, and even reach the ideal capacity of MIMO system.

Investigation into the Performance of a MIMO System Equipped with ULA or UCA Antennas: BER, Capacity and Channel Estimation

This paper reports on investigations into the performance of a Multiple Input Multiple Output (MIMO) wireless communication system employing a uniform linear array (ULA) at the transmitter and either a uni-form linear array (ULA) or a uniform circular array (UCA) antenna at the receiver. The transmitter is as-sumed to be surrounded by scattering objects while the receiver is postulated to be free from scattering ob-jects. The Laplacian distribution of angle of arrival (AOA) of a signal reaching the receiver is postulated. The performance of bit error rate (BER), capacity and channel estimation for a MIMO system are evaluated for the two cases that the receiver is equipped with ULA or with UCA antennas.

On the Capacity of CPM MIMO Systems over Band-Limited Channels

Capacity analysis is a fundamental and important issue for continuous phase modulation (CPM) signals. In the letter, we investigate the capacity formula of CPM MIMO systems. Using Finite State Machine (FSM), the CPM symbols can be modeled as Markov source by combining channel and CPM modulation. Thus the capacity of CPM signals can be derived in form of the erroneous probability and normalized CPM bandwidth. In addition, the capacity of CPM MIMO systems is derived over Gaussian channels and Rayleigh channels. Finally, numerical simulations are implemented according to various parameters such as modulation scheme, modulation index h, memory length L, and antenna configuration.

Capacity Region of a Class of Gaussian Cognitive Degraded Broadcast Channel

This paper studies the cognitive broadcast channel in which the primary user communicates to the primary receiver, while the secondary user has noncausal knowledge of the primary radio's codeword and expects to communicate to two secondary receivers. Comparing with the existing cognitive radio channel which considers only one secondary receiver, cognitive broadcast channel studies the case that there are multiple secondary receivers.To this end, we investigate the fundamental limits of the performance of the Gaussian cognitive broadcast channel from the information theoretic perspective. Specifically, we derive the capacity region of the Gaussian cognitive degraded broadcast channel with weak interference.

Analytical Investigation of Channel Capacity of UWB-MIMO Systems

Ultra-wide-band (UWB) technology combined with multiple input and multiple output (MIMO) provides a viable solution for achieving high data transmission rates of more than 1 Gb/s in wireless communications. UWB is typically applied to short-range indoor environments and is therefore characterized by dense multipath propagation. In this type of environment, MIMO systems allow for a substantial improvement in the spectral efficiency by exploiting the inherent array gain and spatial multiplexing gain of UWB systems. This paper investigates the channel capacity of UWB-MIMO wireless technology and shows that UWB and MIMO designs improve the spectral efficiency logarithmically and linearly, respectively.

Channel Capacity Optimization Based on Riemannian Trust Region Algorithm in IRS-Aided Communication System

Intelligent Reflecting Surface (IRS) can offer unprecedented channel capacity gains since it can reconfigure the signal propagation environment. We decide to maximize the channel capacity by jointly optimizing the transmit-power-constrained precoding matrix at the base station and the unit-modulus-constrained phase shift vector at the IRS in IRS-assisted multi-user downlink communication. We first convert the resulting non-convex problem into an equivalent problem, then use the alternate optimization algorithm. While fixing the phase shift vector, we can obtain the optimal precoding matrix directly by adopting standard optimization packages. While fixing the precoding matrix, we propose the Riemannian Trust-Region (RTR) algorithm to solve this optimization problem. And the key of the RTR algorithm is the solution of the trust-region sub-problem. We first adopt the accurate solution based on Newton's (ASNT) method to solve this sub-problem, which can obtain the global solution but cannot guarantee that the solution is optimal since the initial iteration point is difficult to choose. Then, we propose the Improved-Polyline (IPL) method, which can avoid the difficulty of the ASNT method and improve convergence speed and calculation efficiency. The numerical results show that the RTR algorithm has more significant performance gains and faster convergence speed compared with the existing approaches.

The Influence of LOS Components on the Statistical Properties of the Capacity of Amplify-and-Forward Channels

Amplify-and-forward channels in cooperative networks provide a promising improvement in the network coverage and system throughput. Under line-of-sight (LOS) propagation conditions in such cooperative networks, the overall fading channel can be modeled by a double Rice process. In this article, we have stud-ied the statistical properties of the capacity of double Rice fading channels. We have derived the analytical expressions for the probability density function (PDF), cumulative distribution function (CDF), level- crossing rate (LCR), and average duration of fades (ADF) of the channel capacity. The obtained results are studied for different values of the amplitudes of the LOS components in the two links of double Rice fading channels. It has been observed that the statistics of the capacity of double Rice fading channels are quite dif-ferent from those of double Rayleigh and classical Rice fading channels. Moreover, the presence of an LOS component in any of the two links increases the mean channel capacity and the LCR of the channel capacity. The validity of the theoretical results is confirmed by simulations. The results presented in this article can be very useful for communication system designers to optimize the performance of cooperative networks in wireless communication systems.