In this paper, we study the sum-rate maximization problem in a single-cell massive MIMO downlink system with К users. Unlike the conventional sum-power constraint (SPC) that limits the total average power over all the transmit antennas, the more practical per-antenna power constraint (PAPC) is considered. A precoding scheme based on the principle of equal gain transmission (EGT) is proposed to satisfy any given PAPC with low complexity. We show that as the number of transmit antennas goes to infinity, the gap between the sum-rate achieved by our proposed scheme under PAPC and that under a single SPC achieved with optimal maximum ratio transmission (MRT) approaches k log <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> (4/π) in bits/sec/Hz under the condition of independent Rayleigh fading of the user channels. The analytical results are also verified by numerical examples. Therefore, in massive MIMO systems, our proposed EGT-based precoding scheme is near-optimal under PAPC with asymptotically negligible capacity loss compared against the sum-rate upper bound by the MRT-based precoding under the relaxed SPC, which justifies the use of PAPC in practical massive MIMO systems.
Intelligent reflecting surface (IRS) is envisioned to play a significant role in future wireless communication systems as an effective means of reconfiguring the radio signal propagation environment. In this paper, we study a new multi-IRS aided massive multiple-input multiple-output (MIMO) system, where a multi-antenna BS transmits independent messages to a set of remote single-antenna users using orthogonal beams that are subsequently reflected by different groups of IRSs via their respective multi-hop passive beamforming over pairwise line-of-sight (LoS) links. We aim to select optimal IRSs and their beam routing path for each of the users, along with the active/passive beamforming at the BS/IRSs, such that the minimum received signal power among all users is maximized. This problem is particularly difficult to solve due to a new type of path separation constraints for avoiding the IRS-reflected signal induced interference among different users. To tackle this difficulty, we first derive the optimal BS/IRS active/passive beamforming solutions based on their practical codebooks given the reflection paths. Then we show that the resultant multi-beam multi-hop routing problem can be recast as an equivalent graph-optimization problem, which is however NP-complete. To solve this challenging problem, we propose an efficient recursive algorithm to partially enumerate the feasible routing solutions, which is able to effectively balance the performance-complexity trade-off. Numerical results demonstrate that the proposed algorithm achieves near-optimal performance with low complexity and outperforms other benchmark schemes. Useful insights into the optimal multi-beam multi-hop routing design are also drawn under different setups of the multi-IRS aided massive MIMO network.
Applied the finite volume method combining two-equations turbulence model,the influence of fluid dynamic characteristics on XCP probe under different factors be studied The fluid dynamic characteristics were researched under different influencing factors, such as falling speed, rotating rate,seawater density,etc. The drag coefficient under the different falling speeds and the limited velocity of submarine steady motion were obtained. Compared with the experimental results, the simulated results agree well with experimental results, the experiments have show the validity and feasibility of the numerical analysis method. These results will provide theory reference for selecting the reasonable rotating rate, analyzing stability and the movement rule of probe in the water, choosing suitable test parameters for XCP probe of different seawaters.
In this paper, we study the optimal design for simultaneous wireless information and power transfer (SWIPT) in downlink multiuser orthogonal frequency division multiplexing (OFDM) systems, where the users harvest energy and decode information using the same signals received from a fixed access point (AP). For information transmission, we consider two types of multiple access schemes, namely, time division multiple access (TDMA) and orthogonal frequency division multiple access (OFDMA). At the receiver side, due to the practical limitation that circuits for harvesting energy from radio signals are not yet able to decode the carried information directly, each user applies either time switching (TS) or power splitting (PS) to coordinate the energy harvesting (EH) and information decoding (ID) processes. For the TDMA-based information transmission, we employ TS at the receivers; for the OFDMA-based information transmission, we employ PS at the receivers. Under the above two scenarios, we address the problem of maximizing the weighted sum-rate over all users by varying the time/frequency power allocation and either TS or PS ratio, subject to a minimum harvested energy constraint on each user as well as a peak and/or total transmission power constraint. For the TS scheme, by an appropriate variable transformation the problem is reformulated as a convex problem, for which the optimal power allocation and TS ratio are obtained by the Lagrange duality method. For the PS scheme, we propose an iterative algorithm to optimize the power allocation, subcarrier allocation and the PS ratio for each user. Numerical results show that the peak power constraint imposed on each OFDM subcarrier as well as the number of users in the system play a key role in the rate-energy performance comparison by the two proposed schemes.
In this brief, we present an image entropy coder, context-based bit-plane Golomb coder (CB-BPGC), for wavelet-based scalable image coding. CB-BPGC follows the idea of the state-of-the-art image coding standard JPEG2000 entropy coding to apply the rate-distortion optimization algorithm after block coding. However, it explores a more efficient block coding where statistical properties of the block coefficients are considered. Compression ratio and error resilience performances of the proposed coder are evaluated, and the experimental results show that, compared with the JPEG2000, it achieves better lossless and lossy coding performance with lower complexity and greater resilience to transmission errors when simulated on the wireless Rayleigh fading channel
In order to obtain and use the incomplete information in the power grid fault diagnosis, a unified information model is proposed in this paper. The structure of the model is given, the extended CIM of IEC61970 is employed to describe the primary component topology and component parameters, and IEC61850 is employed to describe the secondary system. Further, the two models are harmonized by OWL. The proposed model can solve the information integrity and standardization issues of fault diagnosis, and make fault diagnosis system practical.
In this paper, capacity limits and power-control schemes are assessed for the block-fading (BF) additive white Gaussian noise (AWGN) channels under the assumption that the channel state information (CSI) is known at both the transmitter and the receiver sides. Two notions of channel capacity limits are considered in this paper, including the ergodic capacity for transmission without delay constraint, and the delay-limited capacity for transmission under a strict delay constraint. With the full availability of CSI, a BF channel can be decomposed into multiple space-time-frequency subchannels, and is, therefore, considered in this paper as a vector BF channel. We propose a class of multitarget (MT) power-control schemes, which we show to be computationally implementable and able to perform well in approaching the capacity limits of vector BF channels. These power-control schemes are based on a subchannel grouping technique, which can be used to further divide subchannels in a vector BF channel into multiple grouped channels, each exhibiting different fading statistics. Each MT scheme then assigns a particular set of power "targets" into these grouped channels, and maximizes the transmission rate via various statistical waterfilling solutions. Numerical results are presented to evaluate and compare the achievable transmission rates associated with these proposed schemes for some example vector BF channels.
The paper studies the transmit optimization problem for MIMO channels with mixed delay-constrained (DC) and no-delay-constrained (NDC) services. Suppose that perfect channel state information is available to both transmitter and receiver sides, we propose a transmission scheme based on a sub-channel grouping (SCG) technique together with different power control policies designed for the grouped channels generated by SCG to support either DC or NDC services. Optimal and sub-optimal power allocation strategies are proposed. Computer simulations are given to evaluate the capacity achieved by the proposed scheme as well as to evaluate the throughput performance when practical bit-loading algorithms are applied.
This paper studies a new decentralized resource allocation strategy, named iterative spectrum shaping (ISS), for the multi-carrier-based multiuser communication system, where two coexisting users independently and sequentially update transmit power allocations over parallel subcarriers to maximize their individual transmit rates. Unlike the conventional iterative water-filling (IWF) algorithm that applies the single-user detection (SD) at each user's receiver by treating the interference from the other user as additional noise, the proposed ISS algorithm applies multiuser detection techniques to decode both the desired user's and interference user's messages if it is feasible, thus termed as opportunistic multiuser detection (OMD). Two encoding methods are considered for ISS: One is carrier independent encoding where independent codewords are modulated by different subcarriers for which different decoding methods can be applied; the other is carrier joint encoding where a single codeword is modulated by all the subcarriers for which a single decoder is applied. For each encoding method, this paper presents the associated optimal user power and rate allocation strategy at each iteration of transmit adaptation. It is shown that under many circumstances the proposed ISS algorithm employing OMD is able to achieve substantial throughput gains over the conventional IWF algorithm employing SD for decentralized spectrum sharing. Applications of ISS in cognitive radio communication systems are also discussed.
We consider the problem of quantifying the Pareto optimal boundary in the achievable rate region over multiple-input single-output (MISO) interference channels, where the problem boils down to solving a sequence of convex feasibility problems after certain transformations. The feasibility problem is solved by two new distributed optimal beamforming algorithms, where the first one is to parallelize the computation based on the method of alternating projections, and the second one is to localize the computation based on the method of cyclic projections. Convergence proofs are established for both algorithms.
In this paper, power-efficient transmission schemes are studied for MIMO-OFDM block-fading channels under the assumption that the channel is perfectly known at the receiver but unknown at the transmitter. Based on the well-known V-BLAST architecture that employs the horizontal encoding and the interference-nulling based successive decoding, this paper presents a closed-loop V-BLAST extension for MIMO-OFDM whereby the transmit rate and power as well as the assigned transmit antenna for each data stream at different OFDM tones are jointly optimized at the receiver and then fed back to the transmitter. Simulation results have confirmed that the closed- loop V-BLAST architecture is able to approach closely the MIMO-OFDM channel capacity attained through the eigenmode transmission that requires the complete channel feedback from the receiver to the transmitter.
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No abstract is provided for this article.
According to the transmission line theory, we proposed the metrology method of S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</sub> phase parameter. The theoretical method has been proved based on the experiments of standard mismatches, Open kit, short kit, air lines and other device. The experiment also find out the law of error distribution, which is that the error's absolute value has negative relationship with the magnitude of reflection coefficient, and the error distribution between opens and short kits is basically symmetrical. Therefore, a 'Residual transmission line' model is proposed which based on mismatches, and the rationality of the model has beenverified by numerical simulation.
Intelligent reflecting surface (IRS) is a promising technology for achieving spectrum and energy efficient wireless networks cost-effectively. Most existing works on IRS have focused on exploiting IRS to enhance the performance of wireless communication or wireless information transmission (WIT), while its potential for boosting the efficiency of radio-frequency (RF) wireless energy transmission (WET) still remains largely open. Although IRS-aided WET shares similar characteristics with IRS-aided WIT, they differ fundamentally in terms of design objective, receiver architecture, and practical constraints. In this paper, we provide a tutorial overview on how to efficiently design IRS-aided WET systems as well as IRS-aided systems with both WIT and WET, namely IRS-aided simultaneous wireless information and power transfer (SWIPT) and IRS-aided wireless powered communication network (WPCN), mainly from a communication and signal processing perspective. In particular, we present state-of-the-art solutions to tackle the unique challenges in operating these systems, such as IRS passive reflection optimization, channel estimation and deployment. In addition, we also propose new solution approaches and point out important directions for future research and investigation.
