Cooperative MIMO channel models: A survey

Cooperative multiple-input multiple-output technology allows a wireless network to coordinate among distributed antennas and achieve considerable performance gains similar to those provided by conventional MIMO systems. It promises significant improvements in spectral efficiency and network coverage and is a major candidate technology in various standard proposals for the fourth-generation wireless communication systems. For the design and accurate performance assessment of cooperative MIMO systems, realistic cooperative MIMO channel models are indispensable. This article provides an overview of the state of the art in cooperative MIMO channel modeling. We show that although the existing standardized point-to-point MIMO channel models can be applied to a certain extent to model cooperative MIMO channels, many new challenges remain in cooperative MIMO channel modeling, such as how to model mobile-to-mobile channels, and how to characterize the heterogeneity and correlation of multiple links at the system level appropriately.     

Exact capacity distribution for dual MIMO systems in Ricean fading

It is well known that multiple input multiple output (MIMO) systems offer the promise of achieving very high spectrum efficiencies (many tens of bit/s/Hz) in a mobile environment. The gains in MIMO capacity are sensitive to the type of channel encountered in the radio environment. To date most analytical work has concentrated on Rayleigh fading channels. Hence, in this letter we consider the capacity outage performance of MIMO systems in Ricean channels. Due to analytical complexity we concentrate on dual antenna systems (either two transmit or two receive antennas) and derive exact densities and distribution functions for the capacity.     

A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach

We introduce a transmit preprocessing technique for the downlink of multiuser multiple-input multiple-output (MIMO) systems. It decomposes the multiuser MIMO downlink channel into multiple parallel independent single-user MIMO downlink channels. Some key properties are that each equivalent single-user MIMO channel has the same properties as a conventional single-user MIMO channel, and that increasing the number of transmit antennas of the multiuser system by one increases the number of spatial channels to each user by one. Simulation results are also provided and these results demonstrate the potential of our technique in terms of performance and capacity.     

Joint antenna selection and link adaptation for MIMO systems

Multi-input multi-output (MIMO) systems, with multiple antennas at both the transmitter and the receiver, are anticipated to be widely employed in future wireless networks due to their predicted tremendous system capacity. To protect the transmitted data against random channel impairment, it is desirable to consider link adaptation, such as rate adaptation and power control, to improve the system performance and guarantee certain quality of service. Based on the observation that link adaptation and antenna selection problems are often coupled, we propose a joint antenna subset selection and link adaptation study for MIMO systems. After the formulation of the multidimensional joint optimization problem, the main contribution of this paper lies in the design of efficient algorithms approaching the optimal solution for both uncorrelated and correlated MIMO channels. Specifically, we propose one simplified antenna selection and link adaptation rule based on the expected optimal number of active antennas for uncorrelated MIMO with Rayleigh fading and one for correlated MIMO channels only based on the slowly varying channel correlation information. Our proposed algorithms are verified through numerical results, demonstrating significant gains over traditional MIMO signaling, while feasible for practical implementation.     

Spatial precoder design for space–time coded MIMO systems: based on fixed parameters of MIMO channels

In realistic channel environments the performance of space–time coded multiple-input multiple output (MIMO) systems is significantly reduced due to non-ideal antenna placement and non-isotropic scattering. In this paper, by exploiting the spatial dimension of a MIMO channel we introduce the novel idea of linear spatial precoding (or power-loading) based on fixed and known parameters of MIMO channels to ameliorate the effects of non-ideal antenna placement on the performance of coherent (channel is known at the receiver) and non-coherent (channel is un-known at the receiver) space–time codes. Antenna spacing and antenna placement (geometry) are considered as fixed parameters of MIMO channels, which are readily known at the transmitter. With this design, the precoder is fixed for fixed antenna placement and the transmitter does not require any feedback of channel state information (partial or full) from the receiver. We also derive precoding schemes to exploit non-isotropic scattering distribution parameters of the scattering channel to improve the performance of space–time codes applied on MIMO systems. However, these schemes require the receiver to estimate the non-isotropic parameters and feed them back to the transmitter. Closed form solutions for precoding schemes are presented for systems with up to three receive antennas. A generalized method is proposed for more than three receive antennas.     

MIMO-OFDM快衰落信道的稀疏自适应感知估计

在多输入多输出（MIMO）-正交频分复用（OFDM） 系统中,怎样在较高频谱利用率的情况下对快时变信道进行较为准确的估计是一个具有挑战性的课题。该文在利用压缩感知理论可提高系统频谱利用率的基础上,提出了一种适合于快时变环境下MIMO-OFDM 系统的稀疏自适应信道估计方法。该方法不再受到奈奎斯特采样频率条件约束,避免了传统导频辅助信道估计方法频谱利用率低的缺点。该文方法通过构建多天线群时频结构特征稀疏基,利用多天线间和群时变OFDM符号内信道冲激响应具有更强稀疏性的特点,对MIMO-OFDM快衰落信道进行稀疏变换。由于实际MIMO-OFDM快衰落信道往往处于频率选择性、时变性和多种干扰并存的复杂环境,受到干扰的信道参数对系统而言是未知,采用该方法克服了现有基于压缩感知理论的信道估计方法需要预先知道信道冲激响应稀疏度才能重构信道参数的不足,在信道稀疏度未知道的情况下,运用稀疏自适应的方法来对不同时频结构特征的信道参数进行估计。仿真结果表明所提估计方法具有对快时变信道参数估计的鲁棒性和较高频谱利用率,且均方误差小。      

Capacity of multiple-antenna fading channels: spatial fading correlation, double scattering, and keyhole

The capacity of multiple-input multiple-output (MIMO) wireless channels is limited by both the spatial fading correlation and rank deficiency of the channel. While spatial fading correlation reduces the diversity gains, rank deficiency due to double scattering or keyhole effects decreases the spatial multiplexing gains of multiple-antenna channels. In this paper, taking into account realistic propagation environments in the presence of spatial fading correlation, double scattering, and keyhole effects, we analyze the ergodic (or mean) MIMO capacity for an arbitrary finite number of transmit and receive antennas. We assume that the channel is unknown at the transmitter and perfectly known at the receiver so that equal power is allocated to each of the transmit antennas. Using some statistical properties of complex random matrices such as Gaussian matrices, Wishart (1928) matrices, and quadratic forms in the Gaussian matrix, we present a closed-form expression for the ergodic capacity of independent Rayleigh-fading MIMO channels and a tight upper bound for spatially correlated/double scattering MIMO channels. We also derive a closed-form capacity formula for keyhole MIMO channels. This analytic formula explicitly shows that the use of multiple antennas in keyhole channels only offers the diversity advantage, but provides no spatial multiplexing gains. Numerical results demonstrate the accuracy of our analytical expressions and the tightness of upper bounds.     

Throughput Analysis for Parallel ARQ over Correlated MIMO Channels

We treat the throughput analyses of parallel ARQ schemes over correlated MIMO channels with adaptive modulation and coding (AMC). To describe the packet transmission over multiple parallel logic channels, we extend the existing burst- error model for single channel to multiple parallel logic channels. Based on such a packet error model, we derive the throughput of different parallel ARQ protocols. Moreover, to describe the temporally correlated physical channel fading, we generalize the existing Markov model for single channel to multiple parallel channels for MIMO systems. Then we develop a method for calculating the packet-level model parameters from the parameters of the physical-layer model and the MIMO transceiver. Using the above hierarchical throughput analysis framework, we investigate the potential throughput gain or throughput loss of parallel ARQ over the conventional serial ARQ in MIMO systems. Our results reveal that as SNR increases, parallel ARQ can achieve higher throughput gain or less throughput loss compared to serial ARQ; parallel SW can achieve throughput gain in most of the MIMO scenarios but increasing the number of antennas does not always bring higher gain; parallel GBN with large number of antennas and independent buffers can achieve throughput gain; parallel SR incurs throughput loss.     

TCP performance over wireless MIMO channels with ARQ and packet combining

Multiple-input multiple-output (MIMO) wireless communication systems that employ multiple transmit and receive antennas can provide very high-rate data transmissions without increase in bandwidth or transmit power. For this reason, MIMO technologies are considered as a key ingredient in the next generation wireless systems, where provision of reliable data services for TCP/IP applications such as wireless multimedia or Internet is of extreme importance. However, while the performance of TCP has been extensively studied over different wireless links, little attention has been paid to the impact of MIMO systems on TCP. This paper provides an investigation on the performance of modern TCP systems when used over wireless channels that employ MIMO technologies. In particular, we focus on two representative categories of MIMO systems, namely, the BLAST systems and the space-time block coding (STBC) systems, and how the ARQ and packet combining techniques impact on the overall TCP performance. We show that, from the TCP throughput standpoint, a more reliable channel may be preferred over a higher spectral efficient but less reliable channel, especially under low SNR conditions. We also study the effect of antenna correlation on the TCP throughput under various conditions.     

Channel capacity of MIMO architecture using the exponentialcorrelation matrix

Multiple-input multiple output (MIMO) communication architecture has recently emerged as a new paradigm for wireless communications in rich multipath environment, which has spectral efficiencies far beyond those offered by conventional techniques. The channel capacity of the MIMO architecture in independent Rayleigh channels scales linearly as the number of antennas. However, the correlation of a real-world wireless channel may result in a substantial degradation of the MIMO architecture performance. In this letter, we investigate the MIMO channel capacity in correlated channels using the exponential correlation matrix model. We prove that, for this model, an increase in correlation is equivalent to a decrease in signal-to-noise ratio (SNR). For example, r=0.7 is the same as 3-dB decrease in SNR     

Optimal antenna selection based on capacity maximization for MIMO systems in correlated channels

Recent work has shown that multiple-input multiple-output (MIMO) systems with multiple antennas at both the transmitter and receiver are able to achieve great capacity improvement. In such systems, it is desirable to select a subset of the available antennas so as to reduce the number of radio frequency (RF) chains. This paper addresses the problem of antenna selection in correlated channels. We consider a narrowband communication system with M transmit and N receive antennas. We present the criterion for selecting the optimal L/sub t/ out of M transmit and L/sub r/ out of N receive antennas in terms of capacity maximization, assuming that only the long-term channel statistics, instead of the instantaneous channel-state information, are known. Simulations will be used to validate our theoretical analysis and demonstrate that the number of required RF chains can be significantly decreased using our proposed selection strategy, while achieving even better performance than the conventional MIMO system without antenna selection.     

A review of antennas and propagation for MIMO wireless communications

Multiple-input-multiple-output (MIMO) wireless systems use multiple antenna elements at transmit and receive to offer improved capacity over single antenna topologies in multipath channels. In such systems, the antenna properties as well as the multipath channel characteristics play a key role in determining communication performance. This paper reviews recent research findings concerning antennas and propagation in MIMO systems. Issues considered include channel capacity computation, channel measurement and modeling approaches, and the impact of antenna element properties and array configuration on system performance. Throughout the discussion, outstanding research questions in these areas are highlighted.     

Degrees of freedom in some underspread MIMO fading channels

Consider a multiple-input multiple-output (MIMO) fading channel in which the fading process varies slowly over time. Assuming that neither the transmitter nor the receiver have knowledge of the fading process, do multiple transmit and receive antennas provide significant capacity improvements at high signal-to-noise ratio (SNR)? For regular fading processes, recent results show that capacity ultimately grows doubly logarithmically with the SNR independently of the number of transmit and receive antennas used. We show that for the Gauss-Markov fading process in all regimes of practical interest the use of multiple antennas provides large capacity improvements. Nonregular fading processes show completely different high-SNR behaviors due to the perfect predictability of the process from noiseless observations. We analyze the capacity of MIMO channels with nonregular fading by presenting a lower bound, which we specialize to the case of band-limited slowly varying fading processes to show that the use of multiple antennas is still highly beneficial. In both cases, regular and nonregular fading, this capacity improvement can be seen as the benefit of having multiple spatial degrees of freedom. For the Gauss-Markov fading model and all regimes of practical interest, we present a communication scheme that achieves the full number of degrees of freedom of the channel with tractable complexity. Our results for underspread Gauss-Markov and band-limited nonregular fading channels suggest that multiple antennas are useful at high SNR.     

Joint Relay and Antenna Selection in MIMO PLNC Inter-vehicular Communication Systems over Cascaded Fading Channels

We investigate the joint relay and antenna selection performance in a multiple input multiple output (MIMO) Vehicle-to-Vehicle (V2V) communication system employing physical layer network coding (PLNC) with amplify-and-forward (AF) scheme at the relay antenna. Analytic results are derived under the cascaded Nakagami-m fading channel model assumption, which covers cascaded Rayleigh and conventional cellular channel models as well. We evaluate the performance of the system in terms of joint outage probability of sources and derive closed-form expressions for lower and upper bounds while an exact expression is found as a single integral form. Besides, the asymptotic diversity order is analyzed and quantified as a function of number of relays and antennas installed on the source and relay vehicles, and channel parameters. Finally, we verify the analytic derivations by computer simulations. Our results show that the outage probability performance decreases with the increasing cascading degrees of the channels but joint relay and antenna selection enhances the performance of the system superbly with the increasing number of relays and antennas. Also it is shown throughout all the simulation results, the lower bound for the joint outage probability seems to consistently be well tight for large SNR. Therefore it can be used for practical design of inter-vehicular communication systems which contain multiple relays and antennas.     

Adaptive transmit antenna selection with pragmatic space-time trellis codes

We consider the problem of selecting a subset of transmit antennas in MIMO systems to minimize error probability when only partial channel information is available at the transmitter. An upper bound for error probability of space-time coded transmit antenna selection scheme conditioned on the channel state information is presented. Based on the performance analysis, a criterion of selecting a subset of available transmit antennas to minimize the upper bound on the PEP is proposed. In contrast to other transmit antenna selection schemes for uncoded transmission or with a fixed number of antennas within the selection subset in the literature, the proposed scheme can adaptively select both a variable number of transmit antennas and their corresponding space-time codes for transmission. Furthermore, we present pragmatic space-time trellis coding schemes for slow Rayleigh fading channels. The principal advantage of the schemes is that a single encoder and decoder can be used for systems with a variable number of transmit antennas. The performance of the pragmatic space-time codes with adaptive antenna selection and the effect of the imperfect channel estimation on performance are evaluated by simulations. It is shown that the adaptive selection offers considerable antenna selection gain relative to the antenna selection system with a fixed number of antennas within the selection subset     

Energy spreading transform based iterative signal detection for mimo fading channels

Multiple transmit and receive antenna arrays can be used to form multiple input and multiple output (MIMO) systems for diversity and multiplexing in wireless communications. In this paper, we develop iterative signal-detection schemes based on energy spreading transform (EST) (T. Hwang and Y. Li) for MIMO channels. The EST in a MIMO system improves signal-detection performance by spreading the symbol energy over the space and time domain. It also enables iterative signal detection without employing channel coding. Analytical and simulation results demonstrate that the performance of the proposed schemes is very close to that of the genie-aided receiver when there are a sufficiently large number of receive antennas and signal-to-noise ratio (SNR) is above a threshold     

Wireless MIMO Sensor Network with Power Constraint WLS/BLUE Estimators

Sensor networks are used in various applications. Sensors acquire samples of physical data and send them to a central node in different topologies to process the data and makes decisions. Multiple Input Multiple Output (MIMO) systems showed good utilization of channel characteristics. In MIMO Sensor Network, multiple signals are transmitted from the sensors and multiple antennas are used at the control node. This provides each receiver the whole combined signal and hence, array processing techniques helps in reducing the effects of noise. In this paper we devise the use of MIMO sensor network and array decision techniques to reduce the noise effect. The proposed Constrained Best Linear Unbiased Estimator (CBLUE) and Constrained Weighted Least Square (CWLS) estimators showed good performance BER when used with MIMO Sensor Network. Most importantly these estimates showed good perturbation results when the estimated channel matrix is not accurate. The condition for good performance was to have the number of receiving antennas at the central node to be equal to the number of transmitting sensors and no significant improve was seen if the number of antennas is greater than the number of transmitting sensors. If the number of sensors is greater than the number of receiving antennas, time or frequency multiplexing is possible to keep good performance for the devised system. Enhancing the BER results in longer battery life at sensor nodes.     

Performance enhancement of multiuser MIMO wireless communication systems

This paper describes a new approach to the problem of enhancing the performance of a multiuser multiple-input-multiple-output (MIMO) system for communication from one base station to many mobile stations in both frequency-flat and frequency-selective fading channels. This problem arises in space-division multiplexing systems with multiple users where many independent signal streams can be transmitted in the same frequency and time slot through the exploitation of multiple antennas at both the base and mobile stations. Our new approach is based on maximizing a lower bound for the product of signal-to-interference plus noise ratio (SINR) of a multiuser MIMO system. This provides a closed-form (noniterative) solution for the antenna weights for all the users, under the constraint of fixed transmit power. Our solution is shown by simulation to have better performance than previously proposed iterative or noniterative solutions. In addition, our solution requires significantly reduced complexity over a gradient search-based method that directly optimizes the product SINRs while still maintaining similar performance. Our solution assumes channel state information is present at the base station or transmitter.     

On the MAC-BC duality of multiuser non-regenerative MIMO relay systems

Multiple input multiple output(MIMO) relaying techniques can greatly improve the spectral efficiency and extend network coverage for future wireless systems.This article investigates a multiuser MIMO relay channel,where a base station(BS) with multiple antennas communicates with multiple mobile stations(MS) via a relay station(RS) with multiple antennas.The RS applies linear processing to the received signal and then forwards the processed signal.The dual channel conditions between MIMO relay multiple access channel(MAC) and broadcast channel(BC) are first developed for single-relay scenario with white Gaussian noise.Then the MAC-BC duality for MIMO relay systems is established by proving that the capacity region of MIMO relay MAC is equal to that of dual MIMO relay BC under the same total network transmit power constraint.In addition,the duality is also extended to multi-relay scenario with arbitrary noise.Finally,several simple general numerical examples are provided to better illustrate the effectiveness of the MIMO relay MAC-BC duality.     

Distributed MIMO Systems for Nomadic Applications Over a Symmetric Interference Channel

A single source communicates with a single destination via a remote wireless multiple-antenna (multiple-input multiple-output (MIMO)) transceiver. The source has access to each of the transmit antennas through a finite-capacity link, and likewise the destination is connected to the receiving antennas via capacity-constrained channels (e.g., as for wired or time-division multiple access (TDMA) channels). Targeting a nomadic communication scenario, in which the remote MIMO transceiver is designed to serve different standards or services, it is assumed that transmitters and receivers are oblivious to the encoding function shared by source and destination. Assuming a Gaussian symmetric interference network as the channel model (as for regularly placed transmitters and receivers), achievable rates are investigated and compared with an upper bound (that holds also for codebook-dependent operation). Closed-form expressions are derived for large numbers of antennas (and in some cases large signal-to-noise ratios (SNRs)), and asymptotics of the achievable rates are studied with respect to either link capacities or SNR. Overall, the analysis points to effective transmission/reception strategies for the distributed MIMO channel at hand, which are optimal under specified conditions. In particular, it is concluded that in certain asymptotic and nonasymptotic regimes there is no loss of optimality in designing the system for nomadic applications (i.e., assuming oblivious transmitters and receivers). Numerical results validate the analysis.