Subcarrier grouping with environmental sensing for MIMO‐OFDM systems over correlated double‐selective fading channels

Multiple‐Input, Multiple‐Output (MIMO)‐orthogonal frequency division multiplexing (OFDM) is a promising technique in 5G wireless communications. In high‐mobility scenarios, the transmission environments are time‐varying and/or the relative moving velocity between the transmitter and receiver is also time‐varying. In the literature, most of previous works mainly focused on fixed subcarrier group size and precoded the MIMO signals with unitary channel state information. In this way, the subcarrier grouping may naturally lead to big loss of channel capacity in high‐mobility scenarios because of the channel state information difference on the subcarriers in each group. To employ the MIMO‐OFDM technique, adaptive subcarrier grouping scheme may be an efficient way. In this paper, we first consider MIMO‐OFDM systems over double‐selective i.i.d. Rayleigh channels and investigate the quantitative relation between subcarrier group size and capacity loss theoretically. With developed theoretical results, we also propose an adaptive subcarrier grouping scheme to satisfy the preset capacity loss threshold by adjusting grouping size with the sensed environmental information and mobile velocity. Theoretical analysis and simulation results show that to achieve a better system capacity, a sparse scattering, lower signal‐to‐noise ratio, and lower velocity as well as properly large antenna number are matched with larger subcarrier group size. One important observation is that if the antenna number is too large and higher than a threshold, which will not bring any additional gain to the subcarrier grouping. That is, the system capacity loss will converge to a lower bound expeditiously with respect to antenna number, which is given in theory also. Copyright © 2016 John Wiley & Sons, Ltd.     

System‐Level Performance of Limited Feedback Schemes for Massive MIMO

To implement high‐order multiuser multiple input and multiple output (MU‐MIMO) for massive MIMO systems, there must be a feedback scheme that can warrant its performance with a limited signaling overhead. The interference‐to‐noise ratio can be a basis for a novel form of Codebook (CB)‐based MU‐MIMO feedback scheme. The objective of this paper is to verify such a scheme's performance under a practical system configuration with a 3D channel model in various radio environments. We evaluate the performance of various CB‐based feedback schemes with different types of overhead reduction approaches, providing an experimental ground with which to optimize a CB‐based MU‐MIMO feedback scheme while identifying the design constraints for a massive MIMO system.     

Design of reduced complexity feedback precoding for MIMO‐OFDM

Beamforming technique is applied to significantly increase the performance of a MIMO system, if the channel information (CI) of the communication system is available at the transmitter. For the transmitter to obtain the entire CI, however, a considerable reverse‐link bandwidth is required. To save the bandwidth, a limited‐rate closed‐loop system, therefore, uses a predetermined codebook which is derived from the CI. The codebook consists of a finite number of precoders out of which the index of the best one is transmitted from the receiver to the transmitter using only a few bits saving substantial bandwidth. However, the amount of bits that need to be fed back can still be significantly large for MIMO‐OFDM systems when the precoding matrix index (PMI) for each subcarrier should be transmitted. Such per‐subcarrier precoding scheme has high feedback overhead and also incurs huge computational cost to determine the best PMI for each subcarrier. We, therefore, propose a per‐band precoding scheme that precodes a band (group) of subcarriers by only one precoder. More importantly, we develop, for the proposed per‐band scheme, reduced‐complexity precoding selection methods that lead to the design of efficient receivers. The effectiveness of the proposed scheme is investigated through computer simulations. Copyright © 2014 John Wiley & Sons, Ltd.     

Bandwidth‐Efficient Selective Retransmission for MIMO‐OFDM Systems

In this work, we propose an efficient selective retransmission method for multiple‐input and multiple‐output (MIMO) wireless systems under orthogonal frequency‐division multiplexing (OFDM) signaling. A typical received OFDM frame may have some symbols in error, which results in a retransmission of the entire frame. Such a retransmission is often unnecessary, and to avoid this, we propose a method to selectively retransmit symbols that correspond to poor‐quality subcarriers. We use the condition numbers of the subcarrier channel matrices of the MIMO‐OFDM system as a quality measure. The proposed scheme is embedded in the modulation layer and is independent of conventional hybrid automatic repeat request (HARQ) methods. The receiver integrates the original OFDM and the punctured retransmitted OFDM signals for more reliable detection. The targeted retransmission results in fewer negative acknowledgements from conventional HARQ algorithms, which results in increasing bandwidth and power efficiency. We investigate the efficacy of the proposed method for optimal and suboptimal receivers. The simulation results demonstrate the efficacy of the proposed method on throughput for MIMO‐OFDM systems.     

Multiuser MIMO receivers for space frequency block coded SC‐FDMA systems

Single carrier‐frequency division multiple access (SC‐FDMA) has been adopted as the uplink transmission standard in fourth generation cellular network to enable the power efficiency transmission in mobile station. Because multiuser MIMO (MU‐MIMO) is a promising technology to fully exploit the channel capacity in mobile radio network, this paper investigates the uplink transmission of SC‐FDMA systems with orthogonal space frequency block codes (SFBC). Two linear MU‐MIMO receivers, orthogonal SFBC (OSFBC) and minimum mean square error (MMSE), are derived for the scenarios with limited number of users or adequate receive antennas at base station. In order to effectively eliminate the multiple access interference (MAI) and fully exploit the capacity of MU‐MIMO channel, we propose a turbo MU‐MIMO receiver, which iteratively utilizes the soft information from maximum a posteriori decoder to cancel the MAI. By the simulation results in several typical MIMO channels, we find that the proposed MMSE MU‐MIMO receiver outperforms the OSFBC receiver over 1 dB at the cost of higher complexity. However, the proposed turbo MU‐MIMO receivers can effectively cancel the MAI under overloaded channel conditions and really achieve the capacity of MU‐MIMO channel. Copyright © 2014 John Wiley & Sons, Ltd.     

EM‐based noise plus interference estimation for OFDM‐based cognitive radio systems

In this paper, we consider the narrowband interference problem for orthogonal frequency division multiplexing (OFDM)‐based cognitive radio (CR) systems, in which parts of the OFDM subcarriers and parts of the data frame can be seriously interfered, resulting in significant performance degradation. We propose a scheme of iterative noise plus interference estimation and decoding (IED) to mitigate the performance degradation caused by the narrowband interference, which is based on expectation maximization (EM) algorithm. To reduce the number of OFDM symbols for time domain averaging required in the proposed scheme, and adapt the proposed scheme to rapid changing narrowband interference conditions, we also propose an IED scheme with frequency domain partial averaging (IED‐FPA). Moreover, we derive the Cramér‐Rao lower bounds for unbiased noise plus interference variance estimations, and they can be achieved via the proposed IED schemes. Simulation results show that the proposed IED‐FPA scheme can effectively achieve the same performance as that of the optimal maximum likelihood decoder with full knowledge of the power plus interference variances, and the proposed IED‐FPA scheme is very robust with respect to the number of the interfered subcarriers and positive errors of the knowledge of the interfered subcarriers' number. Copyright © 2010 John Wiley & Sons, Ltd.     

Novel SINR‐Based User Selection for an MU‐MIMO System with Limited Feedback

This paper presents a novel user selection method based on the signal‐to‐interference‐plus‐noise ratio (SINR), which is approximated using limited feedback data at the base stations (BSs) of multiple user multiple‐input multiple‐output (MU‐MIMO) systems. In the proposed system, the codebook vector index, the quantization error obtained from the correlation between the measured channel and the codebook vector, and the measured value of the largest singular value are fed back from each user to the BS. The proposed method not only generates precoding vectors that are orthogonal to the precoding vectors of the previously selected users and are highly correlated with the codebook vector of each user but also adopts the quantization error in approximating the SINR, which eventually provides a significantly more accurate SINR than the conventional SINR‐based user selection techniques. Computer simulations show that the proposed method enhances the sum rate of the conventional SINR‐based methods by at least 2.4 (2.62) bps/Hz when the number of transmit antennas and number of receive antennas per user terminal is 4 and 1(2), respectively, with 100 candidate users and an SNR of 30 dB.     

Peak‐to‐average power ratio reduction in space–time coded MIMO‐OFDM via preprocessing

In this paper, we propose a trellis exploration algorithm based preprocessing strategy to lower the peak‐to‐average power ratio (PAPR) of precoded MIMO‐OFDM. We first illustrate the degradation in PAPR due to optimal linear precoding in MIMO‐OFDM systems. Then we propose two forms of multi‐layer precoding (MLP) schemes to reduce PAPR. In both schemes, the inner‐layer precoder is designed to optimize system capacity/BER performance. In the first MLP scheme (MLP‐I), a common outer‐layer polyphase precoding matrix is employed. In the second MLP scheme (MLP‐II), data stream corresponding to every transmit antenna is precoded with a different outer‐layer polyphase precoding matrix. Both outer‐layer precoders are custom designed using the trellis exploration algorithm by applying the aperiodic autocorrelation of OFDM data symbols as the metric to minimize. Simulation results indicate that both MLP schemes show superior PAPR performance over conventional MIMO‐OFDM with and without precoding. In addition, MLP better exploits frequency diversity resulting in BER performance gains in multi‐path environments. Copyright © 2010 John Wiley & Sons, Ltd.     

Efficient Near‐Optimal Detection with Generalized Sphere Decoder for Blind MU‐MIMO Systems

In this letter, we propose an efficient near‐optimal detection scheme (that makes use of a generalized sphere decoder (GSD)) for blind multi‐user multiple‐input multiple‐output (MU‐MIMO) systems. In practical MU‐MIMO systems, a receiver suffers from interference because the precoding matrix, the result of the precoding technique used, is quantized with limited feedback and is thus imperfect. The proposed scheme can achieve near‐optimal performance with low complexity by using a GSD to detect several additional interference signals. In addition, the proposed scheme is suitable for use in blind systems.     

Joint Processing of Zero‐Forcing Detection and MAP Decoding for a MIMO‐OFDM System

We propose a new bandwidth‐efficient technique that achieves high data rates over a wideband wireless channel. This new scheme is targeted for a multiple‐input multiple‐output orthogonal frequency‐division multiplexing (MIMO‐OFDM) system that achieves transmit diversity through a space frequency block code and capacity enhancement through the iterative joint processing of zero‐forcing detection and maximum a posteriori (MAP) decoding. Furthermore, the proposed scheme is compared to the coded Bell Labs Layered Space‐Time OFDM (BLAST‐OFDM) scheme.     

On the Capacity and Design of Limited Feedback Multiuser MIMO Uplinks

The theory of multiple-input–multiple-output (MIMO) technology has been well developed to increase fading channel capacity over single-input–single-output (SISO) systems. This capacity gain can often be leveraged by utilizing channel state information at the transmitter and the receiver. Users make use of this channel state information for transmit signal adaptation. In this correspondence, we derive the capacity region for the MIMO multiple access channel (MIMO MAC) when partial channel state information is available at the transmitters, where we assume a synchronous MIMO multiuser uplink. The partial channel state information feedback has a cardinality constraint and is fed back from the basestation to the users using a limited rate feedback channel. Using this feedback information, we propose a finite codebook design method to maximize the sum rate. In this correspondence, the codebook is a set of transmit signal covariance matrices. We also derive the capacity region and codebook design methods in the case that the covariance matrix is rank one (i.e., beamforming). This is motivated by the fact that beamforming is optimal in certain conditions. The simulation results show that when the number of feedback bits increases, the capacity also increases. Even with a small number of feedback bits, the performance of the proposed system is close to an optimal solution with the full feedback.      

A simple soft linear detection for coded multi‐input multi‐output systems

We propose a very simple and efficient soft linear multi‐input multi‐output (MIMO) detection scheme. The detection process is divided into two separate problems. The proposed scheme first detects MIMO symbols using conventional linear detection methods and produces soft bit information using a simple soft demapping method. Next, we refine the soft information by accounting for uneven post‐detection noise variance across MIMO layers. From the simulation result investigated in this paper, we first emphasize that powerful channel coding may suppress the differences of diversity gains among various MIMO detection schemes. This implies that the channel decoding operation may not be transparent to performance gain that resulted from MIMO detection process. The proposed scheme concentrates on accurate estimation of soft post‐MIMO detected information in a very simple manner, rather than concentrating on a complex MIMO detection scheme prior to decoding process. In combination with turbo codes, the proposed scheme produces comparable performance to maximum likelihood detection, even with the simplest scheme such as zero forcing detection, with drastically reduced complexity. Copyright © 2011 John Wiley & Sons, Ltd.     

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

Minimum 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.     

A semi‐definite programming approach to spatial decorrelation of independently polarized signals

A MIMO channel spatial decorrelation scheme based on semi‐definite programming is introduced. As a particular application example, the paper addresses the potential gain of using multiple antennas and MIMO–OFDM techniques in order to increase the bandwidth efficiency in satellite communication systems. In particular, we consider the increase in channel capacity that is possible by exploiting satellite and polarization diversity. A fundamental case is studied with three satellite branches, and where each transmit/receive antenna unit consists of six elemental electric and magnetic dipoles yielding six distinguishable parallel polarization channels per frequency. The numerical examples show that capacity increases linearly on a logarithmic signal‐to‐noise ratio scale where the constant of proportionality is the number of active parallel channels. In this respect, the simultaneous use of triple electric and triple magnetic dipoles has the potential to triple the capacity of an antenna system based on antenna units of single dipoles. Copyright © 2006 John Wiley & Sons, Ltd.     

Progressive intercarrier and co‐channel interference mitigation for underwater acoustic multi‐input multi‐output orthogonal frequency‐division multiplexing

Multi‐input multi‐output orthogonal frequency‐division multiplexing (MIMO‐OFDM) has been actively studied for high data rate communications over the bandwidth‐limited underwater acoustic (UWA) channels. Unlike existing receivers that treat the intercarrier interference (ICI) as additive noise, in this paper, the proposed receiver considers ICI explicitly together with the co‐channel interference (CCI) due to parallel transmissions in MIMO‐OFDM. Using a recently developed progressive receiver framework, the proposed receiver starts with low‐complexity ICI‐ignorant processing and then progresses to ICI‐aware processing with increasing ICI levels. The key components of the proposed receiver include the following: (1) compressed sensing‐based sparse channel estimation, (2) soft‐input soft‐output minimum mean square error/Markov chain Monte Carlo detector for interference mitigation, and (3) soft nonbinary low‐density parity check decoding. In addition to simulation, we use real data from the Surface Processes and Acoustic Communications Experiment 2008 (SPACE08) and the Mobile Acoustic Communications Experiment 2010 (MACE10) to verify the system performance, where the transmitter in SPACE08 was stationary and that in MACE10 was slowly moving. Simulation and experimental results show that explicitly addressing ICI and CCI significantly improves the performance of MIMO‐OFDM in UWA systems. Copyright © 2012 John Wiley & Sons, Ltd.     

Adaptive antennas for MIMO OFDM‐CDMA communication systems

In this paper, we propose symbol‐based receivers for orthogonal frequency division multiplexing (OFDM) code‐division multiple‐access (CDMA) multiple‐input‐multiple‐output (MIMO) communications in multipath fading channels. For multiuser and multipath fading environments, both intersymbol interference and multiple‐access interference must be considered. We propose narrowband and wideband antennas and Wiener code filter for MIMO OFDM‐CDMA systems. The proposed receivers are updated symbol‐by‐symbol to achieve low computational complexity. Simulation results show that the proposed Wiener code filter can improve the system performance for the proposed adaptive antennas. The wideband antenna can achieve better error‐rate performance than that of the narrowband antenna when multipath effect exists. The convergence rate of the recursive least squares antennas is faster than that of the least mean square antennas. Copyright © 2013 John Wiley & Sons, Ltd.     

Impulsive noise estimation and suppression in OFDM systems over in‐home power line channels

This paper proposes a new adaptive iterative method to impulsive noise mitigation in OFDM systems over in‐home power line channels. The performance of impulsive noise mitigation methods based on OFDM decreases when the impulsive noise energy is higher than a certain threshold. To compensate for the limitations of these systems and to be able to adopt it for all sub‐carriers, here, the 64‐QAM constellation is applied together with Alamouti space time coding to transmit, MIMO In‐home power line channel and zero‐forcing estimate (ZFE) with continuous loop impulsive noise detection and mitigation together with maximum‐likelihood detection (MLD) are adopted to receive. At the receiver, after ZFE, impulsive noise detection algorithm based on adaptive threshold for estimating the impulsive noise, determines the locations and amplitudes of the impulsive noises. The effect of impulsive noise on the noise symbols using the mask based on the soft decision method is reduced. Later, using MLD, the original signal is estimated. The algorithm is simulated and analyzed, and its performance is compared to other methods. The results show the superiority and robustness of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.     

Transmission Scheme for 2D Antenna Array MIMO Systems with Limited Feedback

Three-dimensional (3D) multiple-input multiple-output (MIMO) systems exploit spatial richness and provide another degree of freedom to transmit signals and eliminate spatial interference. Currently, however, there is no 3D codebook for two-dimensional (2D) antenna array MIMO systems with limited feedback. In this paper, based on the existing 2D codebook, we present a limited feedback and transmission scheme for 2D antenna array MIMO systems. In this scheme, the mobile station (MS) has imperfect channel knowledge, and the base station (BS) only acquires partial information relating the channel instantiation. MS must feed back two channel state information (CSI) instances, i.e., the horizontal and vertical CSIs. After receiving the two CSI instances, the BS interpolates a new vertical precoding vector using the vertical CSI. Then, the BS re-constructs a 3D beamforming vector using horizontal and vertical precoding vectors and compensates the reported horizontal channel quality indicator. System level simulation is employed, and the simulation results show that the proposed method improves the system spectral efficiency and the cell-edge SE significantly.     

User scheduling based on angles with block diagonalization in MU‐MIMO broadcast

This paper investigates user selection scheme in the multiuser multiple‐input multiple‐output (MU‐MIMO) broadcast (BC) scene with block diagonalization precoding. Block diagonalization is a suboptimal but practical linear precoding method, which can eliminate the multiuser interference by turning the MU‐MIMO BC channel into parallel MIMO channels. With this precoding method, we propose the best user from the user subset to maximize the total throughput in the MU‐MIMO BC system. The angles between subspaces used in this paper are induced from n ‐inner product, an extension from norm space to the n ‐dimensional space, which characterizes the orthogonality between subspaces. One of the algorithms achieves good performance by comparing the capacity greedily, the other one attains high capacity by reducing the cardinality of the user subset to improve the orthogonality between the user channels, which could be seen as a complexity reduction algorithm with respect to the former one. Indeed, they are all based on the angles between subspaces. Analysis shows that both of the proposed algorithms have lower complexity and better performance than the classical algorithms. The numerical results also confirm our analysis.     

Dynamic resource allocation with beamforming for MIMO OFDM systems: performance and effects of imperfect CSI

We propose three different dynamic resource allocation algorithms using adaptive beamforming for multiple-input multiple-output (MIMO) OFDM systems, and investigate their performance over multipath fading channels under perfect and imperfect channel state information (CSI). These approaches involve the use of adaptive modulation, adaptive frequency-domain power allocation, and/or adaptive sub-channel allocation. By employing the proposed approaches in MIMO/OFDM systems, significant performance improvement can be achieved compared to the conventional adaptive antenna array based OFDM. The investigation of the effects of imperfect CSI reveals that the adaptive-modulation based approach is too sensitive to channel estimation errors, and that its performance is worse than the adaptive frequency-domain power allocation and/or adaptive sub-channel allocation approaches. The performance analysis also shows that combining adaptive power allocation with sub-channel allocation yields the best performance under imperfect CSI while being robust to channel estimation errors.