To improve the spectrum efficiency, this paper considers the multiuser detection with the MU-MIMO technology for multiuser MIMO-OFDM system uplink with the same subcarrier shared by multiple users. A low complexity mu...To improve the spectrum efficiency, this paper considers the multiuser detection with the MU-MIMO technology for multiuser MIMO-OFDM system uplink with the same subcarrier shared by multiple users. A low complexity multiuser detection algorithm with recursively successive zero-forcing and successive interference cancellation(RSZF-SIC) based on nullspace is proposed. The RSZF process based on the block diagonalization(BD) technique eliminates the co-channel interference(CCI) by a recursive method based on the nullspace orthogonal theorem. The SIC process detects the user signals respectively with the reasonable user detection sequence based on the results of the RSZF process. The computational complexity of the proposed algorithm is effectively reduced by reducing the total number of singular value decomposition(SVD) operations and the dimension of the SVD matrix in the recursive procedure. The performance of the proposed algorithm is improved in terms of bit error rate and sum capacity of the system, especially in the highSNR regime.展开更多
To minimize the overall transmit power while maintaining a constant data rate and target BER, a downlink adaptive resource allocation algorithm with jointing the exclusive manner and the shared manner is proposed for ...To minimize the overall transmit power while maintaining a constant data rate and target BER, a downlink adaptive resource allocation algorithm with jointing the exclusive manner and the shared manner is proposed for multiuser MIMO-OFDM system in correlated channels. The algorithm allocates all the subcarriers to different users according to their spatial correlations. The users with high spatial correlation are allocated in the same group and the exclusive manner is applied. The shared manner with an improved null broadening method, which improves the performance of co-channel interference （CCI） suppression and decreases the number of transmit antennas required, is applied between the different group users. As the user＇s direction of departure （DOD） changes very slowly, a looking up table method is used to reduce the computational complexity. The simulation results show that despite the angle spread of DOD, when compared with the exclusive manner, the proposed algorithm improves the spectral efficiency, and when compared with the TDMA-ZF （zero forcing） shared manner, the proposed algorithm decreases the total transmit power by at least 1 dB.展开更多
This paper studies the problem of finding an effective subcarrier and power allocation strategy for downlink communication to multiple users in a MIMO-OFDM system with zero-forcing beamforming. The problem of minimizi...This paper studies the problem of finding an effective subcarrier and power allocation strategy for downlink communication to multiple users in a MIMO-OFDM system with zero-forcing beamforming. The problem of minimizing total power consumption with constraint on transmission rate for users is formulated. The problem of joint allocation is divided into two stages. In the first stage, the number of subcarriers that each user will get is determined based on the users’ average signal-to-noise ratio. In the second stage, it finds the best assignment of subcarriers to users. The optimal method is a complex combinatorial problem which can only be assuredly solved through an Exhaustive Search (ES). Since the ES method has high computational com-plexity, the normalized user selection algorithm and the simplified-normalized user selection algorithm are proposed to reduce the computational complexity. Simulation results show that the proposed low complexity algorithms offer better performance compared with an existing algorithm.展开更多
A multiuser Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) broadcast channel is considered where both transmitter and receivers are equipped with multiple antennas. The Channel S...A multiuser Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) broadcast channel is considered where both transmitter and receivers are equipped with multiple antennas. The Channel State Information (CSI) is quantized and provided through limited feedback links. In the first part of this work, the Maximum Expected SINR Combining (MESC) strategy for feedback decrease is investigated. Then a combination of MESC with subcarrier assigning is presented to further reduce the feedback load. The basic idea is the subcarriers are partitioned into resource blocks. For each block, only one quantized channel vector is feedback. The simulation results show MESC can obtain the performance gain over the relevant combiner strategies in MIMO-OFDM system. Moreover the effectiveness on the reduction of feedback overhead by the use of partitioning blocks in the studied system is evaluated.展开更多
We propose an efficient low bit error rate(BER) and low complexity multiple-input multiple-output(MIMO) multiuser detection(MUD) method for use with multiuser MIMO orthogonal frequency division multiplexing(OFDM) syst...We propose an efficient low bit error rate(BER) and low complexity multiple-input multiple-output(MIMO) multiuser detection(MUD) method for use with multiuser MIMO orthogonal frequency division multiplexing(OFDM) systems.It is a hybrid method combining a multiuser-interference-cancellation-based decision feedback equalizer using error feedback filter(MIMO MIC DFE-EFF) and a differential algorithm.The proposed method,termed 'MIMO MIC DFE-EFF with a differential algorithm' for short,has a multiuser feedback structure.We describe the schemes of MIMO MIC DFE-EFF and MIMO MIC DFE-EFF with a differential algorithm,and compare their minimum mean square error(MMSE) performance and computational complexity.Simulation results show that a significant performance gain can be achieved by employing the MIMO MIC DFE-EFF detection algorithm in the context of a multiuser MIMO-OFDM system over frequency selective Rayleigh channel.MIMO MIC DFE-EFF with the differential algorithm improves both computational efficiency and BER performance in a multistage structure relative to conventional DFE-EFF,though there is a small reduction in system performance compared with MIMO MIC DFE-EFF without the differential algorithm.展开更多
To improve the performance of a multiuser MIMO-OFDM system with imperfect channel status information, a downlink adaptive resource allocation algorithm which combines space-time block coding and beam forming （STBC-BF...To improve the performance of a multiuser MIMO-OFDM system with imperfect channel status information, a downlink adaptive resource allocation algorithm which combines space-time block coding and beam forming （STBC-BF） is proposed. The algorithm allocates the subcarriers with a shared manner. A zero forcing processing with joint Rx-Tx is used to suppress the co-channel interference （CCI） and to construct uncorrelated channels for STBC. An adaptive power allocation for the STBC equivalent channels can increase signal to interference and noise ratio at the receiver. Simulation results show that under the condition of an imperfect CSI, the proposed algorithm improves the system performance and reduces the number of BS transmit antennas required.展开更多
Multi Access Interference (MAI) is the main source limiting the capacity and quality of the Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system which fulfills the demand of hig...Multi Access Interference (MAI) is the main source limiting the capacity and quality of the Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system which fulfills the demand of high-speed transmission rate and high quality of service for future underwater acoustic (UWA) communication. Multi User Detection (MUD) is needed to overcome the performance degradation caused by MAI. In this research, both local and global optimal solutions are obtained in Bionic Binary Spotted Hyena Optimizer (BBSHO) algorithm using the Position Coordinate Vectors (PCVs) of the social behavior of spotted hyenas to achieve MUD. Further, Extremal Optimization (EO) is introduced in BBSHO algorithm to improve the local search ability within the search space. Hence, a hybrid BBSHO algorithm is proposed for achieving MUD at the receiver of the MIMO-OFDM system whose transceiver model in underwater is implemented using BELLHOP simulation system. By MATLAB simulation, it is shown that the Bit Error Rate (BER) performance of the proposed hybrid algorithm outperforms with best optimal solution within the search space towards MUD for Interference to Noise Ratio (INR) at 10 dB, 20 dB, and 40 dB over conventional detectors and metaheuristic approaches such as Binary Spotted Hyena Optimizer (BSHO), Binary Particle Swarm Optimization (BPSO) in the UWA network.展开更多
Dual-function communication radar systems use common Radio Frequency(RF)signals are used for both communication and detection.For better compatibility with existing communication systems,we adopt Multiple-Input Multip...Dual-function communication radar systems use common Radio Frequency(RF)signals are used for both communication and detection.For better compatibility with existing communication systems,we adopt Multiple-Input Multiple-Output(MIMO)Orthogonal Frequency Division Multiplexing(OFDM)signals as integrated signals and investigate the estimation performance of MIMO-OFDM signals.First,we analyze the Cramer-Rao Lower Bound(CRLB)of parameter estimation.Then,the transmit powers over different subcarriers are optimized to achieve the best tradeoff between the transmission rate and the estimation performance.Finally,we propose a more accurate estimation method that uses Canonical Polyadic Decomposition(CPD)of the third-order tensor to obtain the parameter matrices.Due to the characteristic of the column structure of the parameter matrices,we only need to use DFT/IDFT to recover the parameters of multiple targets.The simulation results show that tensor-based estimation method can achieve a performance close to CRLB,and the estimation performance can be improved by optimizing the transmit powers.展开更多
In this paper,we focus on the channel estimation for multi-user MIMO-OFDM systems in rich scattering environments.We find that channel sparsity in the delay-angle domain is severely compromised in rich scattering envi...In this paper,we focus on the channel estimation for multi-user MIMO-OFDM systems in rich scattering environments.We find that channel sparsity in the delay-angle domain is severely compromised in rich scattering environments,so that most existing compressed sensing(CS)based techniques can harvest a very limited gain(if any)in reducing the channel estimation overhead.To address the problem,we propose the learning-based turbo message passing(LTMP)algorithm.Instead of exploiting the channel sparsity,LTMP is able to efficiently extract the channel feature via deep learning as well as to exploit the channel continuity in the frequency domain via block-wise linear modelling.More specifically,as a component of LTMP,we develop a multi-scale parallel dilated convolutional neural network(MPDCNN),which leverages frequency-space channel correlation in different scales for channel denoising.We evaluate the LTMP’s performance in MIMO-OFDM channels using the 3rd generation partnership project(3GPP)clustered delay line(CDL)channel models.Simulation results show that the proposed channel estimation method has more than 5 dB power gain than the existing algorithms when the normalized mean-square error of the channel estimation is-20 dB.The proposed algorithm also exhibits strong robustness in various environments.展开更多
MC CDMA is a thriving topic in recent years. Multiuser interference is also very severe as in DS CDMA. ML method is the best multiuser detection, but it has a computational complexity exponentially increased with th...MC CDMA is a thriving topic in recent years. Multiuser interference is also very severe as in DS CDMA. ML method is the best multiuser detection, but it has a computational complexity exponentially increased with the number of users. Mean field annealing and chaotic neural network are two promising optimum techniques. This paper applies them into the ML detection, comparison of the two methods is made.展开更多
The strong noise produced by the leakage of electricity from marine seismic streamers is often received with seismic signals during marine seismic exploration. Traditional denoising methods show unsatisfactory effects...The strong noise produced by the leakage of electricity from marine seismic streamers is often received with seismic signals during marine seismic exploration. Traditional denoising methods show unsatisfactory effects when eliminating strong noise of this kind. Assuming that the strong noise signals have the same statistical properties, a blind source separation （BSS） algorithm is proposed in this paper that results in a new denoising algorithm based on the constrained multi-user kurtosis （MUK） optimization criterion. This method can separate strong noise that shares the same statistical properties as the seismic data records and then eliminate them. Theoretical and field data processing all show that the denoising algorithm, based on multi-user kurtosis optimization criterion, is valid for eliminating the strong noise which is produced by the leakage of electricity from the marine seismic streamer so as to preserve more effective signals and increase the signal-noise ratio. This method is feasible and widely applicable.展开更多
Cell discontinuous transmission(Cell DTx)is a key technology to mitigate inter-cell interference(ICI)in ultra-dense networks(UDNs).The aim of this work is to understand the impact of Cell DTx on physical-layer sum rat...Cell discontinuous transmission(Cell DTx)is a key technology to mitigate inter-cell interference(ICI)in ultra-dense networks(UDNs).The aim of this work is to understand the impact of Cell DTx on physical-layer sum rates of SBSs and link-layer quality-of-service(QoS)performance in multiuser UDNs.In this work,we develop a cross-layer framework for capacity analysis in multiuser UDNs with Cell DTx.In particular,we first extend the traditional one-dimensional effective capacity model to a new multidimensional effective capacity model to derive the sum rate and the effective capacity.Moreover,we propose a new iterative bisection search algorithm that is capable of approximating QoS performance.The convergence of this new algorithm to a unique QoS exponent vector is later proved.Finally,we apply this framework to the round-robin and the max-C/I scheduling policies.Simulation results show that our framework is accurate in approximating 1)queue length distribution,2)delay distribution and 3)sum rates under the above two scheduling policies,and further show that with the Cell DTx,systems have approximately 30% higher sum rate and 35% smaller average delay than those in full-buffer scenarios.展开更多
Reliable, with high data rate, acoustic communication in time-valTing, multipath shallow water environment is a hot research topic recently. Passive time reversal communication has shown promising results in improveme...Reliable, with high data rate, acoustic communication in time-valTing, multipath shallow water environment is a hot research topic recently. Passive time reversal communication has shown promising results in improvement of the system performance. In multiuser environment, the system performance is significantly degraded due to the interference among different users. Passive time reversal can reduce such interference by minimizing the cross-correlated version of channel impulse response among users, which can be realized by the well-separated users in depth. But this method also has its shortcomings, even with the absence of relative motion, the minimization sometimes may be impossible because of the time-varying environment. Therefore in order to avoid the limitation of minimizing the cross-correlated channel function, an approach of passive time reversal based on space-time block coding （STBC） is presented in this paper. In addition, a single channel equalizer is used as a pest processing technique to reduce the residual symbol interference. Experimental results at 13 kHz with 2 kHz bandwidth demonstrate that this method has better performance to decrease bit error rate and improve signal to noise ratio, compared with passive time reversal alone or passive time reversal combined with equalization.展开更多
The main objective of multiuser orthogonal frequency division multiple access(MU-OFDM) is to maximize the total system capacity in wireless communication systems. Thus, the problem in MU-OFDM system is the adaptive al...The main objective of multiuser orthogonal frequency division multiple access(MU-OFDM) is to maximize the total system capacity in wireless communication systems. Thus, the problem in MU-OFDM system is the adaptive allocation of the resources(subcarriers, bits and power) to different users subject to several restrictions to maximize the total system capacity. In this work, a proposed subcarrier allocation algorithm was presented to assign the subcarriers with highest channel gain to the users. After the subcarrier allocation, subcarrier gain-based power allocation(SGPA) was employed for power and bit loading. The simulation results show that the proposed subcarrier-power allocation scheme can achieve high total system capacity and good fairness in allocating the resources to the users with slightly high computational complexity compared to the existing subcarrier allocation algorithms.展开更多
Mobile Edge Computing(MEC)has been envisioned as an efficient solution to provide computation-intensive yet latency-sensitive services for wireless devices.In this paper,we investigate the optimal dynamic spectrum all...Mobile Edge Computing(MEC)has been envisioned as an efficient solution to provide computation-intensive yet latency-sensitive services for wireless devices.In this paper,we investigate the optimal dynamic spectrum allocation-assisted multiuser computation offloading in MEC for overall latency minimization.Specifically,we first focus on a static multiuser computation offloading scenario and jointly optimize users'offloading decisions,transmission durations,and Edge Servers'(ESs)resource allocations.Owing to the nonconvexity of our joint optimization problem,we identify its layered structure and decompose it into two problems:a subproblem and a top problem.For the subproblem,we propose a bisection search-based algorithm to efficiently find the optimal users'offloading decisions and ESs’resource allocations under a given transmission duration.Second,we use a linear search-based algorithm for solving the top problem to obtain the optimal transmission duration based on the result of the subproblem.Further,after solving the static scenario,we consider a dynamic scenario of multiuser computation offloading with time-varying channels and workload.To efficiently address this dynamic scenario,we propose a deep reinforcement learning-based online algorithm to determine the near-optimal transmission duration in a real-time manner.Numerical results are provided to validate our proposed algorithms for minimizing the overall latency in both static and dynamic offloading scenarios.We also demonstrate the advantages of our proposed algorithms compared to the conventional multiuser computation offloading schemes.展开更多
Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple inpu...Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.展开更多
In this paper, the capacity of a multiuser Multiple Input Multiple Output (MIMO) system employing the block diagonalization broadcasting scheme in presence of spatial correlation and mutual coupling is investigated. I...In this paper, the capacity of a multiuser Multiple Input Multiple Output (MIMO) system employing the block diagonalization broadcasting scheme in presence of spatial correlation and mutual coupling is investigated. It is shown by computer simulations that, in general, the presence of spatial correlation decreases the capacity of a multiuser MIMO system. However, for some particular antenna element spacing mutual coupling decreases the spatial correlation rendering an increased capacity. The optimized diagonalization broadcasting technique with a two-stage power allocation scheme is proposed and verified. The presented simulations results confirm the advantage of the proposed broadcasting scheme.展开更多
Due to the openness of wireless multiuser networks,the private information transmitted in uplink or downlink is vulnerable to eavesdropping.Especially,when the downlink transmissions use nonorthogonal multiple access(...Due to the openness of wireless multiuser networks,the private information transmitted in uplink or downlink is vulnerable to eavesdropping.Especially,when the downlink transmissions use nonorthogonal multiple access(NOMA)techniques,the system further encounters interior eavesdropping.In order to address these security problems,we study the secret communication in multiuser networks with both uplink and downlink transmissions.Specifically,in uplink transmissions,the private messages transmitted in each slot are correlated,so any loss of the private information at the eavesdropper will prevent the eavesdropper from decoding the private information in later time slots.In downlink transmissions,the messages are correlated to the uplink information.In this way,any unexpected users who lose the expected user’s uplink information cannot decode its downlink information.The intercept probability is used to measure security performance and we analyze it in theory.Finally,simulation results are provided to corroborate our theoretical analysis.展开更多
基金supported by the Fundamental Research Funds for the Central Universities (Grant No. HIT. NSRIF. 201149)Postdoctoral Science-Research Foundation of Heilongjiang (Grant No. LBH-Q11108)the National Natural Science Foundation of China (61071104)
文摘To improve the spectrum efficiency, this paper considers the multiuser detection with the MU-MIMO technology for multiuser MIMO-OFDM system uplink with the same subcarrier shared by multiple users. A low complexity multiuser detection algorithm with recursively successive zero-forcing and successive interference cancellation(RSZF-SIC) based on nullspace is proposed. The RSZF process based on the block diagonalization(BD) technique eliminates the co-channel interference(CCI) by a recursive method based on the nullspace orthogonal theorem. The SIC process detects the user signals respectively with the reasonable user detection sequence based on the results of the RSZF process. The computational complexity of the proposed algorithm is effectively reduced by reducing the total number of singular value decomposition(SVD) operations and the dimension of the SVD matrix in the recursive procedure. The performance of the proposed algorithm is improved in terms of bit error rate and sum capacity of the system, especially in the highSNR regime.
基金the National Natural Science Foundation of China (60572039 60432040)
文摘To minimize the overall transmit power while maintaining a constant data rate and target BER, a downlink adaptive resource allocation algorithm with jointing the exclusive manner and the shared manner is proposed for multiuser MIMO-OFDM system in correlated channels. The algorithm allocates all the subcarriers to different users according to their spatial correlations. The users with high spatial correlation are allocated in the same group and the exclusive manner is applied. The shared manner with an improved null broadening method, which improves the performance of co-channel interference （CCI） suppression and decreases the number of transmit antennas required, is applied between the different group users. As the user＇s direction of departure （DOD） changes very slowly, a looking up table method is used to reduce the computational complexity. The simulation results show that despite the angle spread of DOD, when compared with the exclusive manner, the proposed algorithm improves the spectral efficiency, and when compared with the TDMA-ZF （zero forcing） shared manner, the proposed algorithm decreases the total transmit power by at least 1 dB.
文摘This paper studies the problem of finding an effective subcarrier and power allocation strategy for downlink communication to multiple users in a MIMO-OFDM system with zero-forcing beamforming. The problem of minimizing total power consumption with constraint on transmission rate for users is formulated. The problem of joint allocation is divided into two stages. In the first stage, the number of subcarriers that each user will get is determined based on the users’ average signal-to-noise ratio. In the second stage, it finds the best assignment of subcarriers to users. The optimal method is a complex combinatorial problem which can only be assuredly solved through an Exhaustive Search (ES). Since the ES method has high computational com-plexity, the normalized user selection algorithm and the simplified-normalized user selection algorithm are proposed to reduce the computational complexity. Simulation results show that the proposed low complexity algorithms offer better performance compared with an existing algorithm.
基金Supported by the National Post-doctoral Research Funding(No.20090451239)
文摘A multiuser Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) broadcast channel is considered where both transmitter and receivers are equipped with multiple antennas. The Channel State Information (CSI) is quantized and provided through limited feedback links. In the first part of this work, the Maximum Expected SINR Combining (MESC) strategy for feedback decrease is investigated. Then a combination of MESC with subcarrier assigning is presented to further reduce the feedback load. The basic idea is the subcarriers are partitioned into resource blocks. For each block, only one quantized channel vector is feedback. The simulation results show MESC can obtain the performance gain over the relevant combiner strategies in MIMO-OFDM system. Moreover the effectiveness on the reduction of feedback overhead by the use of partitioning blocks in the studied system is evaluated.
基金supported by the National Science and Technology Pillar Program (Nos 2008BAH30B12 and 2008BAH30B09)the Important National Science and Technology Specific Projects (Nos 2008ZX 03003-004, 2009ZX03003-008, 2009ZX03003-009, and 2009ZX 03002-009)+1 种基金the National Natural Science Foundation of China (No 60802009)the National High-Tech R & D Program (863) of China (Nos 2008AA01Z204 and 2009AA01Z205)
文摘We propose an efficient low bit error rate(BER) and low complexity multiple-input multiple-output(MIMO) multiuser detection(MUD) method for use with multiuser MIMO orthogonal frequency division multiplexing(OFDM) systems.It is a hybrid method combining a multiuser-interference-cancellation-based decision feedback equalizer using error feedback filter(MIMO MIC DFE-EFF) and a differential algorithm.The proposed method,termed 'MIMO MIC DFE-EFF with a differential algorithm' for short,has a multiuser feedback structure.We describe the schemes of MIMO MIC DFE-EFF and MIMO MIC DFE-EFF with a differential algorithm,and compare their minimum mean square error(MMSE) performance and computational complexity.Simulation results show that a significant performance gain can be achieved by employing the MIMO MIC DFE-EFF detection algorithm in the context of a multiuser MIMO-OFDM system over frequency selective Rayleigh channel.MIMO MIC DFE-EFF with the differential algorithm improves both computational efficiency and BER performance in a multistage structure relative to conventional DFE-EFF,though there is a small reduction in system performance compared with MIMO MIC DFE-EFF without the differential algorithm.
基金supported partly by the Postdoctoral Science Foundation of Chinathe National Natural Science Foundation of China(60572039).
文摘To improve the performance of a multiuser MIMO-OFDM system with imperfect channel status information, a downlink adaptive resource allocation algorithm which combines space-time block coding and beam forming （STBC-BF） is proposed. The algorithm allocates the subcarriers with a shared manner. A zero forcing processing with joint Rx-Tx is used to suppress the co-channel interference （CCI） and to construct uncorrelated channels for STBC. An adaptive power allocation for the STBC equivalent channels can increase signal to interference and noise ratio at the receiver. Simulation results show that under the condition of an imperfect CSI, the proposed algorithm improves the system performance and reduces the number of BS transmit antennas required.
文摘Multi Access Interference (MAI) is the main source limiting the capacity and quality of the Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system which fulfills the demand of high-speed transmission rate and high quality of service for future underwater acoustic (UWA) communication. Multi User Detection (MUD) is needed to overcome the performance degradation caused by MAI. In this research, both local and global optimal solutions are obtained in Bionic Binary Spotted Hyena Optimizer (BBSHO) algorithm using the Position Coordinate Vectors (PCVs) of the social behavior of spotted hyenas to achieve MUD. Further, Extremal Optimization (EO) is introduced in BBSHO algorithm to improve the local search ability within the search space. Hence, a hybrid BBSHO algorithm is proposed for achieving MUD at the receiver of the MIMO-OFDM system whose transceiver model in underwater is implemented using BELLHOP simulation system. By MATLAB simulation, it is shown that the Bit Error Rate (BER) performance of the proposed hybrid algorithm outperforms with best optimal solution within the search space towards MUD for Interference to Noise Ratio (INR) at 10 dB, 20 dB, and 40 dB over conventional detectors and metaheuristic approaches such as Binary Spotted Hyena Optimizer (BSHO), Binary Particle Swarm Optimization (BPSO) in the UWA network.
基金supported by the National Natural Science Foundation of China under grants 62072229,U1936201,62071220,61976113joint project of China Mobile Research Institute&X-NET。
文摘Dual-function communication radar systems use common Radio Frequency(RF)signals are used for both communication and detection.For better compatibility with existing communication systems,we adopt Multiple-Input Multiple-Output(MIMO)Orthogonal Frequency Division Multiplexing(OFDM)signals as integrated signals and investigate the estimation performance of MIMO-OFDM signals.First,we analyze the Cramer-Rao Lower Bound(CRLB)of parameter estimation.Then,the transmit powers over different subcarriers are optimized to achieve the best tradeoff between the transmission rate and the estimation performance.Finally,we propose a more accurate estimation method that uses Canonical Polyadic Decomposition(CPD)of the third-order tensor to obtain the parameter matrices.Due to the characteristic of the column structure of the parameter matrices,we only need to use DFT/IDFT to recover the parameters of multiple targets.The simulation results show that tensor-based estimation method can achieve a performance close to CRLB,and the estimation performance can be improved by optimizing the transmit powers.
基金supported in part by the National Key Research and Development Program of China under Grant 2020YFB1804800.
文摘In this paper,we focus on the channel estimation for multi-user MIMO-OFDM systems in rich scattering environments.We find that channel sparsity in the delay-angle domain is severely compromised in rich scattering environments,so that most existing compressed sensing(CS)based techniques can harvest a very limited gain(if any)in reducing the channel estimation overhead.To address the problem,we propose the learning-based turbo message passing(LTMP)algorithm.Instead of exploiting the channel sparsity,LTMP is able to efficiently extract the channel feature via deep learning as well as to exploit the channel continuity in the frequency domain via block-wise linear modelling.More specifically,as a component of LTMP,we develop a multi-scale parallel dilated convolutional neural network(MPDCNN),which leverages frequency-space channel correlation in different scales for channel denoising.We evaluate the LTMP’s performance in MIMO-OFDM channels using the 3rd generation partnership project(3GPP)clustered delay line(CDL)channel models.Simulation results show that the proposed channel estimation method has more than 5 dB power gain than the existing algorithms when the normalized mean-square error of the channel estimation is-20 dB.The proposed algorithm also exhibits strong robustness in various environments.
文摘MC CDMA is a thriving topic in recent years. Multiuser interference is also very severe as in DS CDMA. ML method is the best multiuser detection, but it has a computational complexity exponentially increased with the number of users. Mean field annealing and chaotic neural network are two promising optimum techniques. This paper applies them into the ML detection, comparison of the two methods is made.
基金supported by the National Natural Science Foundation of China(No. 41176077)the State Oceanic Administration Young Marine Science Foundation(No. 2013702)
文摘The strong noise produced by the leakage of electricity from marine seismic streamers is often received with seismic signals during marine seismic exploration. Traditional denoising methods show unsatisfactory effects when eliminating strong noise of this kind. Assuming that the strong noise signals have the same statistical properties, a blind source separation （BSS） algorithm is proposed in this paper that results in a new denoising algorithm based on the constrained multi-user kurtosis （MUK） optimization criterion. This method can separate strong noise that shares the same statistical properties as the seismic data records and then eliminate them. Theoretical and field data processing all show that the denoising algorithm, based on multi-user kurtosis optimization criterion, is valid for eliminating the strong noise which is produced by the leakage of electricity from the marine seismic streamer so as to preserve more effective signals and increase the signal-noise ratio. This method is feasible and widely applicable.
文摘Cell discontinuous transmission(Cell DTx)is a key technology to mitigate inter-cell interference(ICI)in ultra-dense networks(UDNs).The aim of this work is to understand the impact of Cell DTx on physical-layer sum rates of SBSs and link-layer quality-of-service(QoS)performance in multiuser UDNs.In this work,we develop a cross-layer framework for capacity analysis in multiuser UDNs with Cell DTx.In particular,we first extend the traditional one-dimensional effective capacity model to a new multidimensional effective capacity model to derive the sum rate and the effective capacity.Moreover,we propose a new iterative bisection search algorithm that is capable of approximating QoS performance.The convergence of this new algorithm to a unique QoS exponent vector is later proved.Finally,we apply this framework to the round-robin and the max-C/I scheduling policies.Simulation results show that our framework is accurate in approximating 1)queue length distribution,2)delay distribution and 3)sum rates under the above two scheduling policies,and further show that with the Cell DTx,systems have approximately 30% higher sum rate and 35% smaller average delay than those in full-buffer scenarios.
基金supported by the National Natural Science Foundation of China(Grant Nos.60772094 and 60872066)
文摘Reliable, with high data rate, acoustic communication in time-valTing, multipath shallow water environment is a hot research topic recently. Passive time reversal communication has shown promising results in improvement of the system performance. In multiuser environment, the system performance is significantly degraded due to the interference among different users. Passive time reversal can reduce such interference by minimizing the cross-correlated version of channel impulse response among users, which can be realized by the well-separated users in depth. But this method also has its shortcomings, even with the absence of relative motion, the minimization sometimes may be impossible because of the time-varying environment. Therefore in order to avoid the limitation of minimizing the cross-correlated channel function, an approach of passive time reversal based on space-time block coding （STBC） is presented in this paper. In addition, a single channel equalizer is used as a pest processing technique to reduce the residual symbol interference. Experimental results at 13 kHz with 2 kHz bandwidth demonstrate that this method has better performance to decrease bit error rate and improve signal to noise ratio, compared with passive time reversal alone or passive time reversal combined with equalization.
文摘The main objective of multiuser orthogonal frequency division multiple access(MU-OFDM) is to maximize the total system capacity in wireless communication systems. Thus, the problem in MU-OFDM system is the adaptive allocation of the resources(subcarriers, bits and power) to different users subject to several restrictions to maximize the total system capacity. In this work, a proposed subcarrier allocation algorithm was presented to assign the subcarriers with highest channel gain to the users. After the subcarrier allocation, subcarrier gain-based power allocation(SGPA) was employed for power and bit loading. The simulation results show that the proposed subcarrier-power allocation scheme can achieve high total system capacity and good fairness in allocating the resources to the users with slightly high computational complexity compared to the existing subcarrier allocation algorithms.
基金supported in part by the Joint Scientific Research Project Funding Scheme between Macao Science and Technology Development Fund and the Ministry of Science and Technology of the People's Republic of China under Grant 0066/2019/AMJin part by the Intergovernmental International Cooperation in Science and Technology Innovation Program under Grants 2019YFE0111600+3 种基金in part by the Macao Science and Technology Development Fund under Grants 0060/2019/A1 and 0162/2019/A3in part by National Natural Science Foundation of China under Grant 62072490in part by Research Grant of University of Macao under Grants MYRG2018-00237-FST and SRG2019-00168-IOTSCin part by FDCT SKL-IOTSC(UM)-2021-2023.
文摘Mobile Edge Computing(MEC)has been envisioned as an efficient solution to provide computation-intensive yet latency-sensitive services for wireless devices.In this paper,we investigate the optimal dynamic spectrum allocation-assisted multiuser computation offloading in MEC for overall latency minimization.Specifically,we first focus on a static multiuser computation offloading scenario and jointly optimize users'offloading decisions,transmission durations,and Edge Servers'(ESs)resource allocations.Owing to the nonconvexity of our joint optimization problem,we identify its layered structure and decompose it into two problems:a subproblem and a top problem.For the subproblem,we propose a bisection search-based algorithm to efficiently find the optimal users'offloading decisions and ESs’resource allocations under a given transmission duration.Second,we use a linear search-based algorithm for solving the top problem to obtain the optimal transmission duration based on the result of the subproblem.Further,after solving the static scenario,we consider a dynamic scenario of multiuser computation offloading with time-varying channels and workload.To efficiently address this dynamic scenario,we propose a deep reinforcement learning-based online algorithm to determine the near-optimal transmission duration in a real-time manner.Numerical results are provided to validate our proposed algorithms for minimizing the overall latency in both static and dynamic offloading scenarios.We also demonstrate the advantages of our proposed algorithms compared to the conventional multiuser computation offloading schemes.
文摘Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.
文摘In this paper, the capacity of a multiuser Multiple Input Multiple Output (MIMO) system employing the block diagonalization broadcasting scheme in presence of spatial correlation and mutual coupling is investigated. It is shown by computer simulations that, in general, the presence of spatial correlation decreases the capacity of a multiuser MIMO system. However, for some particular antenna element spacing mutual coupling decreases the spatial correlation rendering an increased capacity. The optimized diagonalization broadcasting technique with a two-stage power allocation scheme is proposed and verified. The presented simulations results confirm the advantage of the proposed broadcasting scheme.
基金supported in part by the Fundamental Research Funds for the Central Universities(No.21620350)in part by the National Natural Science Foundation of China(No.62102167 and No.62032025)in part by the Guangdong Basic and Applied Basic Research Foundation(2020A1515110364).
文摘Due to the openness of wireless multiuser networks,the private information transmitted in uplink or downlink is vulnerable to eavesdropping.Especially,when the downlink transmissions use nonorthogonal multiple access(NOMA)techniques,the system further encounters interior eavesdropping.In order to address these security problems,we study the secret communication in multiuser networks with both uplink and downlink transmissions.Specifically,in uplink transmissions,the private messages transmitted in each slot are correlated,so any loss of the private information at the eavesdropper will prevent the eavesdropper from decoding the private information in later time slots.In downlink transmissions,the messages are correlated to the uplink information.In this way,any unexpected users who lose the expected user’s uplink information cannot decode its downlink information.The intercept probability is used to measure security performance and we analyze it in theory.Finally,simulation results are provided to corroborate our theoretical analysis.
