Multiuser Multiple-input Multiple-output Orthogonal Frequency Division Multiplexing Research Articles

Target location and velocity estimation with the multistatic MU‐MIMO‐OFDM modulation signal

AbstractIn passive radar and joint communication and radar sensing (JCRS), target sensing with the multiuser multiple input multiple output orthogonal frequency division multiplexing (MU‐MIMO‐OFDM) modulation signal is gaining increasing interest. Multiple transmit nodes emitting the MU‐MIMO‐OFDM modulation signals at the same carrier frequency and one receiver collecting the target‐reflected signals for target location and velocity estimation are considered. This is a typical scenario when using the fifth‐generation (5G) communication network signal for target sensing. In this scenario, the echo signals corresponding to different transmit nodes are not resolved in the receiver, and the modulated data symbols cannot be removed from the received signals. Most traditional parameter estimation methods in passive radar and JCRS may not be suitable here. A location and velocity estimation method with the received echo signals is proposed. Specifically, the location parameters are extracted directly from the received echo signals. The location estimation is cast into a block sparse vector reconstruction problem. The variational Bayesian sparsity learning (VBSL) method is exploited for the reconstruction of the block sparse vector. Accelerated VBSL methods are developed for improving the computational efficiency. Simulations verify the effectiveness of the proposed methods.

Performance analysis of multiuser MIMO OFDM systems incorporating feedback delay and feedback error

In multiuser Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems the performance can be improved when full Channel State Information (CSI) is available at the transmitter. The characterization of downlink channel is estimated at the receiver and feedback to the transmitter. But the transmitter may acquire false information due to delay or errors in the feedback channel. The resulting channel capacity loss and Bit Error Rate (BER) performance are evaluated. The BER and the capacity of MIMO-OFDM systems are analyzed by varying the parameters of the system.

Joint Resource Allocation and Transceiver Design for Sum-Rate Maximization Under Latency Constraints in Multicell MU-MIMO Systems

Due to the continuous advancements of orthogonal frequency division multiplexing (OFDM) and multiple antenna techniques, multiuser multiple input multiple output (MU-MIMO) OFDM is a key enabler of both fourth and fifth generation networks. In this paper, we consider the problem of weighted sum-rate maximization under latency constraints in finite buffer multicell MU-MIMO OFDM systems. Unlike previous works, the optimization variables include the transceiver beamforming vectors, the scheduled packet size and the resources in the frequency and power domains. This problem is motivated by the observation that multicell MU-MIMO OFDM systems serve multiple quality of service classes and the system performance depends critically on both the transceiver design and the scheduling algorithm. Since this problem is non-convex, we resort to the max-plus queuing method and successive convex approximation. We propose both centralized and decentralized solutions, in which practical design aspects, such as signaling overhead, are considered. Finally, we compare the proposed framework with state-of-the-art algorithms in relevant scenarios, assuming a realistic channel model with space, frequency and time correlations. Numerical results indicate that our design provides significant gains over designs based on the wide-spread saturated buffers assumption, while also outperforming algorithms that consider a finite-buffer model. Due to the continuous advancements of orthogonal frequency division multiplexing (OFDM) and multiple antenna techniques, multiuser multiple input multiple output (MU-MIMO) OFDM is a key enabler of both fourth and fifth generation networks. In this paper, we consider the problem of weighted sum-rate maximization under latency constraints in finite buffer multicell MU-MIMO OFDM systems. Unlike previous works, the optimization variables include the transceiver beamforming vectors, the scheduled packet size and the resources in the frequency and power domains. This problem is motivated by the observation that multicell MU-MIMO OFDM systems serve multiple quality of service classes and the system performance depends critically on both the transceiver design and the scheduling algorithm. Since this problem is non-convex, we resort to the max-plus queuing method and successive convex approximation. We propose both centralized and decentralized solutions, in which practical design aspects, such as signaling overhead, are considered. Finally, we compare the proposed framework with state-of-the-art algorithms in relevant scenarios, assuming a realistic channel model with space, frequency and time correlations. Numerical results indicate that our design provides significant gains over designs based on the wide-spread saturated buffers assumption, while also outperforming algorithms that consider a finite-buffer model.

A Downlink Multiuser MIMO–OFDM System With Nonideal Oscillators and Amplifiers: Characterization and Performance Analysis

In this article, we analytically investigate the performance of a downlink multiuser (MU) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system with hardware impairments. Specifically, we focus on the joint impact of nonideal oscillators and nonlinear high-power amplifiers, which can be quantified in terms of multiplicative and additive nonlinear distortions as well as phase noise, which causes inter-channel interference (ICI). We first derive the signal-to-distortion-plus-interference-plus-noise ratio (SDINR) and then utilize the SDINR to derive the closed-form expressions for symbol-error-rate and the average capacity of the aforementioned system. Our analysis shows that the statistics of an additive nonlinear distortion and additive white Gaussian noise are not affected by phase noise. However, the phase noise itself significantly deteriorates the performance of the MU-MIMO-OFDM system even in the absence of the nonlinear distortions. We further show that nonlinear distortion and ICI cause an irreducible error floor which considerably degrades the system error performance and also adversely affects the total capacity of the MU-MIMO-OFDM system. Comparisons are drawn between the performance of an ideal MU-MIMO-OFDM system and a MU-MIMO-OFDM system in presence of above impairments. In the end, we present the simulation results to validate the efficacy of our theoretical analysis.

Influence of optimal pair-wise SUS algorithm on MU-MIMO-OFDM system performance

In this paper we proposed a new user scheduling algorithm, named as optimal pair-wise semi-orthogonal user selection (SUS), for multiuser multiple-input multiple-output orthogonal frequency division multiplexing (MU-MIMO-OFDM) system. Multiuser interferences are canceled applying zero-forcing beamforming (ZFBF) technique with presumption that channel state is perfectly known at transmit side. Simulated throughput and error results demonstrate advantage gain achieved in system performance realised through applying the proposed scheduling algorithm.

Performance Analysis of Linear Precoded MU-MIMO-OFDM Systems With Nonlinear Power Amplifiers and Correlated Channel

In this paper, we investigate the effect of power amplifier (PA) nonlinearity on a multi user multiple-input multiple-output orthogonal frequency division multiplexing (MU-MIMO-OFDM) system where the base station (BS) uses linear precoding to transmit data for single antenna users through a correlated channel. The signal to distortion, interference and noise ratio is derived for any order of PA nonlinearity. Our analysis shows that a correlated channel can result in correlated distortions at the output of PAs which increase the received distortion power of users. Approximations for the ergodic achievable rate of the users are provided when the BS transmits data through a correlated channel using maximum ratio transmission or zero forcing precodings and number of BS antennas and users are large. Also, closed form approximations for the ergodic achievable sum rate of the system are provided when the channel is not correlated. The simulation results agree with the derived approximations even when the number of transmit antennas and users are relatively small. The approximations can be used to find the achievable sum rate maximizing number of users or transmit power of the system.

A Receiving Antenna Allocation Scheme for Downlink MU-MIMO-OFDM Transmission

This paper proposes a novel receiving antenna allocation scheme for downlink multiuser multiple input multiple output orthogonal frequency division multiplexing (MU-MIMO-OFDM) transmission; an access point (AP) simultaneously transmits data frames to a combination of allocated receiving antennas on a subcarrier basis at each station (STA). The proposed scheme combines a limited channel state information (CSI) feedback sequence with a receiving antenna decision method. In the proposed scheme, each STA estimates the channel responses of all receiving antennas by using the training preamble transmitted from an AP, and then feeds the channel response of the antenna with maximum norm back to the AP when the spatial correlation value between receiving antennas is higher than a threshold. Otherwise, each STA feeds full channel responses back to the AP. This scheme decreases the amount of CSI fed back while exploiting the spatial diversity gain, and the AP’s computational complexity is also decreased regarding the antenna allocation. Moreover, the receiving antenna decision method eliminates the overhead to notify the allocated antenna information from the AP to each STA by simply comparing its own receiving antenna powers. We clarify the effectiveness of the proposed scheme in our computer simulations using channel responses measured in an indoor environment. The results show that the proposed scheme maintains the channel capacity of the downlink MU-MIMO-OFDM transmission while greatly reducing the overhead and computational complexity.

Resource Allocation in Multi-User MIMO-OFDM Systems with Double-objective Optimization

A resource allocation algorithm is proposed in this paper to simultaneously minimize the total system power consumption and maximize the system throughput for the downlink of multi-user multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems. With the Lagrange dual decomposition method, we transform the original problem to its convex dual problem and prove that the duality gap between the two problems is zero, which means the optimal solution of the original problem can be obtained by solving its dual problem. Then, we use convex optimization method to solve the dual problem and utilize bisection method to obtain the optimal dual variable. The numerical results show that the proposed algorithm is superior to traditional single-objective optimization method in both the system throughput and the system energy consumption.

Subcarrier and Power Allocation for Multiuser MIMO-OFDM Systems with Various Detectors

Resource allocation plays a crucial role in multiuser multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems to improve overall system performance. While previously proposed resource allocation algorithms are mainly designed from the point of view of the information-theoretic, we formulate the resource allocation problem as an average bit error rate (BER) minimization problem subject to a total power constraint when considering employing realistic MIMO detection techniques. Subsequently, we derive the optimal subcarrier and power allocation algorithms for three types of well-known MIMO detectors, including the maximum likelihood (ML) detector, linear detectors, and successive interference cancellation (SIC) detectors. To reduce the complexity, we also propose a two-step suboptimal algorithm that separates subcarrier and power allocation for each detector. We also analyze the diversity gain of the proposed suboptimal algorithms for various MIMO detectors. Simulation results confirm that the proposed suboptimal algorithm for each detector can achieve a comparable performance with the optimal allocation with a much lower complexity. Moreover, it is shown that the suboptimal algorithms perform better than the conventional algorithms that are known in the literature.

A Novel Subspace Based Method for Compensation of Multiple CFOs in Uplink MIMO OFDM Systems

The tri-linear data model for an arbitrary multi-user uplink multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system comprising orthogonal frequency division multiplexing access users and co-channel (CC) users is formulated in this letter. A novel subspace-based method for multi-access interference cancellation and CC data separation in multi-user MIMO OFDM systems, utilizing the independent manifolds spanned by user’s carrier frequency offset matrix, is proposed in this letter. The system constraints under which the proposed subspace nulling method works are derived, which includes the under-determined cases, where minimum mean square error/zero forcing methods fail.

Multi user MIMO‐OFDM‐based power line communication structure with hardware impairments and crosstalk

Broadband power line communication (BPLC) provides high speed data services without requiring the installation of new infrastructure. Multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) technology can significantly improve the BPLC performance. In this study a new multi-user (MU) MIMO-OFDM structure for BPLC is proposed. The effects of physical hardware impairments on the performance of this structure are also presented. Unlike to MIMO-BPLC with ideal hardware, the hardware impairments cause a capacity limit at high signal-to-noise ratio (SNR). Another technical challenge in designing MIMO BPLC network is the crosstalk between MIMO PLC ports which has non-negligible effect on network capacity. In order to reduce the effects of crosstalk, the authors propose a new scheme based on applying Pre-coding at the transmitter before applying the singular value decomposition (SVD) on the MIMO channel. Due to the nature of the power-line channel, the different users have different channel conditions. Thus this study also addresses the application of an efficient resource allocation algorithm to improve the overall performance of the proposed BPLC structure. The obtained results indicate that by applying the proposed resource allocation algorithm along with the Maximum Ratio Combining Pre-coding (Pre-MRC), the proposed structure becomes insensitive to crosstalk and has significant channel capacity compared to conventional PLC networks.

LS Channel Estimation in Multicell Multiuser MIMO OFDM with Zadoff Chu Sequence as Pilots

High spectral efficiency and the ability to combat multipath fading are the key requirements of future wireless communication systems. Multiple-input multiple-output (MIMO) combined with orthogonal frequency- division multiplexing (OFDM) has been widely considered to be a promising candidate. Moreover Multi user MIMO OFDM can provide good spatial multiplexing with single antenna for each user. In the case of multicell multiuser MIMO OFDM system main challenge is to acquire the channel state information. In order to get the channel state information, channel estimation is to be done. Here pilot aided LS channel estimation is used to obtain the estimates. For multi cell multi user MIMO OFDM, channel estimation using pilot subcarriers causes pilot contamination. This is due to the reuse of pilot subcarriers in different cells. In order to reduce the impact of pilot contamination, pilot sequences must select properly. Here Zadoff Chu sequences are used for the design of pilots in different cells.

Adaptive robust Max-SLNR precoder for MU-MIMO-OFDM systems with imperfect CSI

The accuracy of channel state information (CSI) available at a base station (BS) has a direct impact on the performance of precoding in wideband multi-user multiple input, multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems and depends on many factors, including: the delay between estimation and beamforming at the BS (also called the CSI delay), Doppler spread, the channel estimation method used, the average transmit power of pilot symbols, and the average number of pilot symbols that must be estimated per channel parameter. In this paper, the coefficient of CSI error needed to adapt to fading channels is modeled as a function of Doppler spread, CSI delay, and signal-to-noise ratio (SNR). In terms of the Gaussian-Markov CSI error model, an adaptive robust maximum signal-to-leakage-and-noise ratio (Max- SLNR) precoder is designed to track the statistical parameters of CSI error. The Doppler spread and SNR can be obtained through real-time estimation based on orthogonal pilot patterns. Simulation results show that, compared to non-adaptive robust and non-robust precoders of Max-SLNR, the proposed adaptive robust Max- SLNR precoder performs much better in terms of bit error rate (BER). Moreover, as either the average number of training symbols per channel parameter or the average transmit power increases, the BER performance of the proposed precoder approaches that of a precoder with ideal CSI.

Sub-channel shared resource allocation for multi-user distributed MIMO-OFDM systems

Well-controlled resource allocation is crucial for promoting the performance of multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Recent studies have focused primarily on traditional centralized systems or distributed antenna systems (DASs), and usually assumed that one sub-carrier or sub-channel is exclusively occupied by one user. To promote system performance, we propose a sub-channel shared resource allocation algorithm for multi-user distributed MIMO-OFDM systems. Each sub-channel can be shared by multiple users in the algorithm, which is different from previous algorithms. The algorithm assumes that each user communicates with only two best ports in the system. On each sub-carrier, it allocates a sub-channel in descending order, which means one sub-channel that can minimize signal to leakage plus noise ratio (SLNR) loss is deleted until the number of remaining sub-channels is equal to that of receiving antennas. If there are still sub-channels after all users are processed, these sub-channels will be allocated to users who can maximize the SLNR gain. Simulations show that compared to other algorithms, our proposed algorithm has better capacity performance and enables the system to provide service to more users under the same capacity constraints.

Analysis of minimum transmit sum power and scheduling power gain for multi‐user MIMO‐OFDM networks with rate constraints

ABSTRACTMinimum transmit sum power (MTSP) is of high theoretical and practical value in multi‐user rate‐constrained systems; it is, however, quite difficult to be numerically characterized in complex channels for the prohibitively high computational power required. In this paper, we present a computationally efficient method to approximate the MTSP in multi‐user multiple‐input multiple‐output orthogonal frequency division multiplexing (MU‐MIMO‐OFDM) wireless networks. Specifically, we propose both lower and upper bounds of the MTSP, which are asymptotically accurate in the limit of large K, the number of users. Then, we develop two iterative water‐filling algorithms to numerically solve the proposed bounds. These algorithms are with low complexity, that is, linear in K, and therefore enable the analysis of MTSP in complex channels even if K is large. Numerical results demonstrate the effectiveness of the bounds in approximating the MTSP and the high computational efficiency of the proposed iterative water‐filling algorithms. With the proposed bounds, we further numerically study scheduling power gain (SPG), which is defined as MTSP reduction achieved by scheduling resources over multiple channel blocks in time domain. We simulate the SPG in different wireless environments defined in Third Generation Partnership Project spatial channel extended model and find insignificant SPG in some cases, indicating that the benefit from scheduling over multiple channel blocks is limited and simply allocating resources within the present channel is sufficient. Our analysis on the MTSP and SPG provides guidelines on the design of resource schedulers in MU‐MIMO‐OFDM networks. Copyright © 2014 John Wiley & Sons, Ltd.

Scalable Resource Allocation for SVC Video Streaming Over Multiuser MIMO-OFDM Networks

In this paper, we propose a scalable resource allocation framework for streaming scalable videos over multiuser multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) networks. We exploit the utilities of scalable videos produced by the scalable extension of H.264/AVC (SVC) and investigate the multidimensional diversities of the multiuser MIMO-OFDM wireless networks. First, we study the rate-utility relationship of SVC via a packet prioritization scheme. Based on the rate-utility analysis, a scalable resource-allocation framework is proposed to achieve differentiated service objectives for different scalable video layers. To provide users with fair opportunities to acquire basic viewing experience, a fair scheme is designed to guarantee that each user is entitled to a MAXMIN fairness to have their base layer video packets received. After all users have their base layer packets successfully scheduled, resources are distributed to exploit the network efficiency. The two schemes are integrated into a unified bit loading and power allocation solution to enhance the practicability of the scalable framework. Experiment results confirms that the proposed scheme handles fairness and efficiency better at different scenarios than the conventional schemes.

IDMA for the Multiuser MIMO-OFDM Uplink: A Factor Graph Framework for Joint Data Detection and Channel Estimation

Interleave-division multiple access (IDMA) has recently been proposed as a promising alternative to code-division multiple access (CDMA). In this paper, we consider the use of IDMA within a multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) multiuser system employing higher-order modulation and transmitting over frequency-selective MIMO channels. Based on a factor graph/message passing framework and the sum-product algorithm, we devise an iterative receiver that jointly performs pilot-aided channel estimation, multiuser detection, and channel decoding. The use of Gaussian message approximations results in a receiver complexity that scales only linearly with the number of users. A further complexity reduction is obtained by a novel selective message updating scheme. We also present a simulation-based comparison of the maximum rate achievable with our MIMO-OFDM-IDMA receiver with the information-theoretic capacity of the multiple-access channel. Finally, we provide simulation results illustrating the bit error rate (BER) performance of our receiver. It is observed that the proposed turbo-like integration of channel estimation in the iterative multiuser detection and channel decoding scheme yields a dramatic BER reduction, and that the proposed selective message updating scheme results in a significant reduction of complexity.

Development and experimental validation of downlink multiuser MIMO-OFDM in gigabit wireless LAN systems

Multiuser multiple-input multiple-output (MU-MIMO) has been proposed as a means to improve spectrum efficiency for various future wireless communication systems. This paper reports indoor experimental results obtained for a newly developed and implemented downlink (DL) MU-MIMO orthogonal frequency division multiplexing (OFDM) transceiver for gigabit wireless local area network systems in the microwave band. In the transceiver, the channel state information (CSI) is estimated at each user and fed back to an access point (AP) on a real-time basis. At the AP, the estimated CSI is used to calculate the transmit beamforming weight for DL MU-MIMO transmission. This paper also proposes a recursive inverse matrix computation scheme for computing the transmit weight in real time. Experiments with the developed transceiver demonstrate its feasibility in a number of indoor scenarios. The experimental results clarify that DL MU-MIMO-OFDM transmission can achieve a 972-Mbit/s transmission data rate with simple digital signal processing of single-antenna users in an indoor environment.

Analysis and Comparison of Compensation Techniques of HPA Nonlinearity in Multi-User MIMO OFDM Systems using MMSE Receiver

The combination of Multiple Input Multiple Output (MIMO) with Orthogonal Frequency Division Multiplexing (OFDM) is a promising technique for high performance with very high data rates in 4G broadband wireless communications. However, the non-linearities caused by the High Power Amplifier (HPA) degrade the performance of MIMO-OFDM systems. In this paper, we present a theoretical analysis of nonlinear (NL) distortion effects in a MIMO-OFDM system in terms of error probability and system Capacity. Then, two compensators for reducing the distortion are proposed. The first is based on neural networks and the second is an iterative technique called Power Amplifier Nonlinearty Cancellation (PANC). These techniques correct the nonlinear distortion effects on the received signal, accompanied with MMSE detector. This receiver has shown best performance comparing to other receivers [1]. Simulation results show the comparison between the theoretical and simulated of nonlinear distortion effects in MIMO-OFDM transmission systems, as well as the performance of different compensators.

Iterative receivers with channel estimation for multi-user MIMO-OFDM: complexity and performance

A family of iterative receivers is evaluated in terms of complexity and performance for the case of an uplink multi-user (MU) multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. The transmission over block fading channels is considered. The analyzed class of receivers is performing channel estimation inside the iterative detection loop, which has been shown to improve estimation performance. As part of our results we illustrate the ability of this type of receiver to reduce the required amount of pilot symbols. A remaining question to ask is which combinations of estimation and detection algorithms that provide the best trade-off between performance and complexity. We address this issue by considering MU detectors and channel estimators, with varying algorithm complexity. For MU detection, two algorithms based on parallel interference cancellation (PIC) are considered and compared with the optimal symbol-wise maximum a-posteriori probability (MAP) detector. For channel estimation, an algorithm performing joint minimum-mean-square-error (MMSE) estimation is considered along with a low complexity replica making use of a Krylov subspace method. An estimator based on the space alternating generalized expectation-maximization (SAGE) algorithm is also considered. Our results show that low-complexity algorithms provide the best tradeoff, even though more receiver iterations are needed to reach a desired performance.