Showing papers on "MIMO published in 2010"

Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas

Abstract: A cellular base station serves a multiplicity of single-antenna terminals over the same time-frequency interval. Time-division duplex operation combined with reverse-link pilots enables the base station to estimate the reciprocal forward- and reverse-link channels. The conjugate-transpose of the channel estimates are used as a linear precoder and combiner respectively on the forward and reverse links. Propagation, unknown to both terminals and base station, comprises fast fading, log-normal shadow fading, and geometric attenuation. In the limit of an infinite number of antennas a complete multi-cellular analysis, which accounts for inter-cellular interference and the overhead and errors associated with channel-state information, yields a number of mathematically exact conclusions and points to a desirable direction towards which cellular wireless could evolve. In particular the effects of uncorrelated noise and fast fading vanish, throughput and the number of terminals are independent of the size of the cells, spectral efficiency is independent of bandwidth, and the required transmitted energy per bit vanishes. The only remaining impairment is inter-cellular interference caused by re-use of the pilot sequences in other cells (pilot contamination) which does not vanish with unlimited number of antennas.

Multi-Cell MIMO Cooperative Networks: A New Look at Interference

Abstract: This paper presents an overview of the theory and currently known techniques for multi-cell MIMO (multiple input multiple output) cooperation in wireless networks. In dense networks where interference emerges as the key capacity-limiting factor, multi-cell cooperation can dramatically improve the system performance. Remarkably, such techniques literally exploit inter-cell interference by allowing the user data to be jointly processed by several interfering base stations, thus mimicking the benefits of a large virtual MIMO array. Multi-cell MIMO cooperation concepts are examined from different perspectives, including an examination of the fundamental information-theoretic limits, a review of the coding and signal processing algorithmic developments, and, going beyond that, consideration of very practical issues related to scalability and system-level integration. A few promising and quite fundamental research avenues are also suggested.

Secure Transmission With Multiple Antennas—Part II: The MIMOME Wiretap Channel

Abstract: The capacity of the Gaussian wiretap channel model is analyzed when there are multiple antennas at the sender, intended receiver and eavesdropper. The associated channel matrices are fixed and known to all the terminals. A computable characterization of the secrecy capacity is established as the saddle point solution to a minimax problem. The converse is based on a Sato-type argument used in other broadcast settings, and the coding theorem is based on Gaussian wiretap codebooks. At high signal-to-noise ratio (SNR), the secrecy capacity is shown to be attained by simultaneously diagonalizing the channel matrices via the generalized singular value decomposition, and independently coding across the resulting parallel channels. The associated capacity is expressed in terms of the corresponding generalized singular values. It is shown that a semi-blind "masked" multi-input multi-output (MIMO) transmission strategy that sends information along directions in which there is gain to the intended receiver, and synthetic noise along directions in which there is not, can be arbitrarily far from capacity in this regime. Necessary and sufficient conditions for the secrecy capacity to be zero are provided, which simplify in the limit of many antennas when the entries of the channel matrices are independent and identically distributed. The resulting scaling laws establish that to prevent secure communication, the eavesdropper needs three times as many antennas as the sender and intended receiver have jointly, and that the optimum division of antennas between sender and intended receiver is in the ratio of 2:1.

MIMO-OFDM Wireless Communications with MATLAB

Abstract: MIMO-OFDM is a key technology for next-generation cellular communications (3GPP-LTE, Mobile WiMAX, IMT-Advanced) as well as wireless LAN (IEEE 802.11a, IEEE 802.11n), wireless PAN (MB-OFDM), and broadcasting (DAB, DVB, DMB). In MIMO-OFDM Wireless Communications with MATLAB, the authors provide a comprehensive introduction to the theory and practice of wireless channel modeling, OFDM, and MIMO, using MATLAB programs to simulate the various techniques on MIMO-OFDM systems. One of the only books in the area dedicated to explaining simulation aspects Covers implementation to help cement the key concepts Uses materials that have been classroom-tested in numerous universities Provides the analytic solutions and practical examples with downloadable MATLAB codes Simulation examples based on actual industry and research projects Presentation slides with key equations and figures for instructor use MIMO-OFDM Wireless Communications with MATLAB is a key text for graduate students in wireless communications. Professionals and technicians in wireless communication fields, graduate students in signal processing, as well as senior undergraduates majoring in wireless communications will find this book a practical introduction to the MIMO-OFDM techniques. Instructor materials and MATLAB code examples available for download at www.wiley.com/go/chomimo

Full-duplex wireless communications using off-the-shelf radios: Feasibility and first results

Abstract: We study full-duplex wireless communication systems where same band simultaneous bidirectional communication is achieved via cancellation of the self-interfering signal Using off-the-shelf MIMO radios, we present experimental results that characterize the suppression performance of three self-interference cancellation mechanisms, which combine a different mix of analog and digital cancellation Our experimental results show that while the amount of self-interference increases linearly with the transmitted power, the self-interference can be sufficiently cancelled to make full-duplex wireless communication feasible in many cases Our experimental results further show that if the self-interference is cancelled in the analog domain before the interfering signal reaches the receiver front end, then the resulting full-duplex system can achieve rates higher than the rates achieved by a half-duplex system with identical analog resources

On Feasibility of Interference Alignment in MIMO Interference Networks

Abstract: We explore the feasibility of interference alignment in signal vector space-based only on beamforming-for K-user MIMO interference channels. Our main contribution is to relate the feasibility issue to the problem of determining the solvability of a multivariate polynomial system which is considered extensively in algebraic geometry. It is well known, e.g., from Bezout's theorem, that generic polynomial systems are solvable if and only if the number of equations does not exceed the number of variables. Following this intuition, we classify signal space interference alignment problems as either proper or improper based on the number of equations and variables. Rigorous connections between feasible and proper systems are made through Bernshtein's theorem for the case where each transmitter uses only one beamforming vector. The multibeam case introduces dependencies among the coefficients of a polynomial system so that the system is no longer generic in the sense required by both theorems. In this case, we show that the connection between feasible and proper systems can be further strengthened (since the equivalency between feasible and proper systems does not always hold) by including standard information theoretic outer bounds in the feasibility analysis.

Predictable 802.11 packet delivery from wireless channel measurements

Abstract: RSSI is known to be a fickle indicator of whether a wireless link will work, for many reasons. This greatly complicates operation because it requires testing and adaptation to find the best rate, transmit power or other parameter that is tuned to boost performance. We show that, for the first time, wireless packet delivery can be accurately predicted for commodity 802.11 NICs from only the channel measurements that they provide. Our model uses 802.11n Channel State Information measurements as input to an OFDM receiver model we develop by using the concept of effective SNR. It is simple, easy to deploy, broadly useful, and accurate. It makes packet delivery predictions for 802.11a/g SISO rates and 802.11n MIMO rates, plus choices of transmit power and antennas. We report testbed experiments that show narrow transition regions (

Coordinated multipoint transmission/reception techniques for LTE-advanced [Coordinated and Distributed MIMO]

Abstract: This article presents an elaborate coordination technique among multiple cell sites called coordinated multipoint transmission and reception in the Third Generation Partnership Project for LTE-Advanced. After addressing major radio access techniques in the LTE Release 8 specifications, system requirements and applied radio access techniques that satisfy the requirements for LTE-Advanced are described including CoMP transmission and reception. Then CoMP transmission and reception schemes and the related radio interface, which were agreed upon or are currently being discussed in the 3GPP, are presented. Finally, system-level simulation evaluations show that the CoMP transmission and reception schemes have a significant effect in terms of improving the cell edge user throughput based on LTE-Advanced simulation conditions.

Multiuser MIMO Achievable Rates With Downlink Training and Channel State Feedback

Abstract: In this paper, we consider a multiple-input-multiple-output (MIMO) fading broadcast channel and compute achievable ergodic rates when channel state information (CSI) is acquired at the receivers via downlink training and it is provided to the transmitter by channel state feedback. Unquantized (analog) and quantized (digital) channel state feedback schemes are analyzed and compared under various assumptions. Digital feedback is shown to be potentially superior when the feedback channel uses per channel state coefficient is larger than 1. Also, we show that by proper design of the digital feedback link, errors in the feedback have a minor effect even if simple uncoded modulation is used on the feedback channel. We discuss first the case of an unfaded additive white Gaussian noise (AWGN) feedback channel with orthogonal access and then the case of fading MIMO multiple access (MIMO-MAC). We show that by exploiting the MIMO-MAC nature of the uplink channel, a much better scaling of the feedback channel resource with the number of base station (BS) antennas can be achieved. Finally, for the case of delayed feedback, we show that in the realistic case where the fading process has (normalized) maximum Doppler frequency shift 0 ? F < 1/2, a fraction 1 - 2F of the optimal multiplexing gain is achievable. The general conclusion of this work is that very significant downlink throughput is achievable with simple and efficient channel state feedback, provided that the feedback link is properly designed.

System Level Simulation of LTE Networks

Abstract: In order to evaluate the performance of new mobile network technologies, system level simulations are crucial. They aim at determining whether, and at which level predicted link level gains impact network performance. In this paper we present a MATLAB computationally efficient LTE system level simulator. The simulator is offered for free under an academic, noncommercial use license, a first to the authors' knowledge. The simulator is capable of evaluating the performance of the Downlink Shared Channel of LTE SISO and MIMO networks using Open Loop Spatial Multiplexing and Transmission Diversity transmit modes. The physical layer model is based on the postequalization SINR and provides the simulation pre-calculated "fading parameters" representing each of the individual interference terms. This structure allows the fading parameters to be pregenerated offline, vastly reducing computational complexity at run-time.

Generalised spatial modulation

Abstract: In this paper, a generalised technique for spatial modulation (SM) is presented. Generalised spatial modulation (GSM) overcomes in a novel fashion the constraint in SM that the number of transmit antennas has to be a power of two. In GSM, a block of information bits is mapped to a constellation symbol and a spatial symbol. The spatial symbol is a combination of transmit antennas activated at each instance. The actual combination of active transmit antennas depends on the random incoming data stream. This is unlike SM where only a single transmit antenna is activated at each instance. GSM increases the overall spectral efficiency by base-two logarithm of the number of antenna combinations. This reduces the number of transmit antennas needed for the same spectral efficiency. The performance of GSM is analysed in this paper, and an upper bound on the bit-error-ratio (BER) performance is derived. In addition, an algorithm to optimise the antenna combination selection is proposed. Finally, the performance of GSM is validated through Monte Carlo simulations. The results are compared with traditional SM. It is shown that for the same spectral efficiency GSM performs nearly the same as SM, but with a significant reduction in the number of transmit antennas.

Completely Stale Transmitter Channel State Information is Still Very Useful

Abstract: Transmitter channel state information (CSIT) is crucial for the multiplexing gains offered by advanced interference management techniques such as multiuser MIMO and interference alignment. Such CSIT is usually obtained by feedback from the receivers, but the feedback is subject to delays. The usual approach is to use the fed back information to predict the current channel state and then apply a scheme designed assuming perfect CSIT. When the feedback delay is large compared to the channel coherence time, such a prediction approach completely fails to achieve any multiplexing gain. In this paper, we show that even in this case, the completely stale CSI is still very useful. More concretely, we show that in a MIMO broadcast channel with $K$ transmit antennas and $K$ receivers each with 1 receive antenna, $\frac{K}{1+1/2+ ...+ \frac{1}{K}} (> 1) $ degrees of freedom is achievable even when the fed back channel state is completely independent of the current channel state. Moreover, we establish that if all receivers have independent and identically distributed channels, then this is the optimal number of degrees of freedom achievable. In the optimal scheme, the transmitter uses the fed back CSI to learn the side information that the receivers receive from previous transmissions rather than to predict the current channel state. Our result can be viewed as the first example of feedback providing a degree-of-freedom gain in memoryless channels.

MIMO techniques in WiMAX and LTE: a feature overview

Abstract: IEEE 802.16m and 3GPP LTE-Advanced are the two evolving standards targeting 4G wireless systems. In both standards, multiple-input multiple-output antenna technologies play an essential role in meeting the 4G requirements. The application of MIMO technologies is one of the most crucial distinctions between 3G and 4G. It not only enhances the conventional point-to-point link, but also enables new types of links such as downlink multiuser MIMO. A large family of MIMO techniques has been developed for various links and with various amounts of available channel state information in both IEEE 802.16e/m and 3GPP LTE/LTE-Advanced. In this article we provide a survey of the MIMO techniques in the two standards. The MIMO features of the two are compared, and the engineering considerations are depicted.

Direction of Departure (DOD) and Direction of Arrival (DOA) Estimation in MIMO Radar with Reduced-Dimension MUSIC

Abstract: This letter discusses the problem of direction of departure (DOD) and direction of arrival (DOA) estimation for multi-input multi-output (MIMO) radar, and derives a reduced-dimension multiple signal classification (MUSIC) algorithm therein. The proposed algorithm, which only requires one-dimension search, can avoid the high computational cost within two-dimension MUSIC (2D-MUSIC) algorithm. We illustrate that the algorithm has better performance ESPRIT algorithm, and has very close performance to 2D-MUSIC algorithm. Further our algorithm requires no pair matching. Simulation results verify the usefulness of our algorithm.

Target Localization Accuracy Gain in MIMO Radar-Based Systems

Abstract: This paper presents an analysis of target localization accuracy, attainable by the use of multiple-input multiple-output (MIMO) radar systems, configured with multiple transmit and receive sensors, widely distributed over an area. The Cramer-Rao lower bound (CRLB) for target localization accuracy is developed for both coherent and noncoherent processing. Coherent processing requires a common phase reference for all transmit and receive sensors. The CRLB is shown to be inversely proportional to the signal effective bandwidth in the noncoherent case, but is approximately inversely proportional to the carrier frequency in the coherent case. We further prove that optimization over the sensors' positions lowers the CRLB by a factor equal to the product of the number of transmitting and receiving sensors. The best linear unbiased estimator (BLUE) is derived for the MIMO target localization problem. The BLUE's utility is in providing a closed-form localization estimate that facilitates the analysis of the relations between sensors locations, target location, and localization accuracy. Geometric dilution of precision (GDOP) contours are used to map the relative performance accuracy for a given layout of radars over a given geographic area.

Degrees of Freedom of the $K$ User $M \times N$ MIMO Interference Channel

Abstract: We provide inner bound and outer bound for the total number of degrees of freedom of the K user multiple-input multiple-output (MIMO) Gaussian interference channel with M antennas at each transmitter and N antennas at each receiver if the channel coefficients are time-varying and drawn from a continuous distribution. The bounds are tight when the ratio [(max(M,N))/(min(M,N))]=R is equal to an integer. For this case, we show that the total number of degrees of freedom is equal to min(M,N)K if K ≤ R and min(M,N)[(R)/(R+1)]K if K > R. Achievability is based on interference alignment. We also provide examples where using interference alignment combined with zero forcing can achieve more degrees of freedom than merely zero forcing for some MIMO interference channels with constant channel coefficients.

Phased-MIMO Radar: A Tradeoff Between Phased-Array and MIMO Radars

Abstract: We propose a new technique for multiple-input multiple-output (MIMO) radar with colocated antennas which we call phased-MIMO radar. The new technique enjoys the advantages of the MIMO radar without sacrificing the main advantage of the phased-array radar which is the coherent processing gain at the transmitting side. The essence of the proposed technique is to partition the transmit array into a number of subarrays that are allowed to overlap. Then, each subarray is used to coherently transmit a waveform which is orthogonal to the waveforms transmitted by other subarrays. Coherent processing gain can be achieved by designing a weight vector for each subarray to form a beam towards a certain direction in space. Moreover, the subarrays are combined jointly to form a MIMO radar resulting in higher angular resolution capabilities. Substantial improvements offered by the proposed phased-MIMO radar technique as compared to the phased-array and MIMO radar techniques are demonstrated analytically and by simulations through analyzing the corresponding beam patterns and the achievable output signal-to-noise-plus-interference ratios. Both analytical and simulation results validate the effectiveness of the proposed phased-MIMO radar.

Vehicle integrated communications system

Abstract: A novel and useful vehicle integrated communications system that provides a solution to the poor performance experienced at the cell edge in a cellular communications system due to weak signal strength and high interference levels. A core cellular communications platform embedded (integrated) into the vehicle platform utilizes multiple antennas integrated into the body of the vehicle which are coupled to a multi-antenna transceiver; receives electrical power from the vehicle power source eliminating the limitations of hand held device batteries; processes multiple MIMO RF signals taking advantage of antenna diversity, beamforming and spatial multiplexing; executes advanced interference mitigation algorithms; implements adaptive modulation and coding algorithms; and utilizes dynamic channel modeling and estimation to significantly improve performance. The core cellular link functions as a platform for any number of vehicle based applications including a smart vehicle repeater, mobile femtocell, inverted femtocell and vehicle infotainment system.

Analog Beamforming in MIMO Communications With Phase Shift Networks and Online Channel Estimation

Abstract: In multiple-input multiple-output (MIMO) systems, the use of many radio frequency (RF) and analog-to-digital converter (ADC) chains at the receiver is costly. Analog beamformers operating in the RF domain can reduce the number of antenna signals to a feasible number of baseband channels. Subsequently, digital beamforming is used to capture the desired user signal. In this paper, we consider the design of the analog and digital beamforming coefficients, for the case of narrowband signals. We aim to cancel interfering signals in the analog domain, thus minimizing the required ADC resolution. For a given resolution, we will propose the optimal analog beamformer to minimize the mean squared error between the desired user and its receiver estimate. Practical analog beamformers employ only a quantized number of phase shifts. For this case, we propose a design technique to successively approximate the desired overall beamformer by a linear combination of implementable analog beamformers. Finally, an online channel estimation technique is introduced to estimate the required statistics of the wireless channel on which the optimal beamformers are based.

Cooperative Multicell Precoding: Rate Region Characterization and Distributed Strategies With Instantaneous and Statistical CSI

Abstract: Base station cooperation is an attractive way of increasing the spectral efficiency in multiantenna communication. By serving each terminal through several base stations in a given area, intercell interference can be coordinated and higher performance achieved, especially for terminals at cell edges. Most previous work in the area has assumed that base stations have common knowledge of both data dedicated to all terminals and full or partial channel state information (CSI) of all links. Herein, we analyze the case of distributed cooperation where each base station has only local CSI, either instantaneous or statistical. In the case of instantaneous CSI, the beamforming vectors that can attain the outer boundary of the achievable rate region are characterized for an arbitrary number of multiantenna transmitters and single-antenna receivers. This characterization only requires local CSI and justifies distributed precoding design based on a novel virtual signal-to-interference noise ratio (SINR) framework, which can handle an arbitrary SNR and achieves the optimal multiplexing gain. The local power allocation between terminals is solved heuristically. Conceptually, analogous results for the achievable rate region characterization and precoding design are derived in the case of local statistical CSI. The benefits of distributed cooperative transmission are illustrated numerically, and it is shown that most of the performance with centralized cooperation can be obtained using only local CSI.

Cooperative Algorithms for MIMO Interference Channels

Abstract: Interference alignment is a transmission technique for exploiting all available degrees of freedom in the interference channel with an arbitrary number of users. Most prior work on interference alignment, however, neglects interference from other nodes in the network not participating in the alignment operation. This paper proposes three generalizations of interference alignment for the multiple-antenna interference channel with multiple users that account for colored noise, which models uncoordinated interference. First, a minimum interference-plus-noise leakage algorithm is presented, and shown to be equivalent to previous subspace methods when noise is spatially white or negligible. A joint minimum mean squared error design is then proposed that jointly optimizes the transmit precoders and receive spatial filters, whereas previous designs neglect the receive spatial filter. This algorithm is shown to be a generalization of previous joint MMSE designs for other system configurations such as the broadcast channel. Finally, a maximum signal-to-interference-plus-noise ratio algorithm is developed that is proven to converge, unlike previous maximum SINR algorithms. The latter two designs are shown to have increased complexity due to non-orthogonal precoders, more required iterations, or more channel state knowledge than the min INL or subspace methods. The sum throughput performance of these algorithms is simulated in the context of a network with uncoordinated co-channel interferers not participating in the alignment protocol. It is found that a network with cochannel interference can benefit from employing precoders designed to consider that interference, but in some cases, ignoring the co-channel interference is advantageous.

Multiuser Two-Way Amplify-and-Forward Relay Processing and Power Control Methods for Beamforming Systems

Abstract: In this paper, multiple-input multiple-output (MIMO) relay transceiver processing is proposed for multiuser two-way relay communications. The relay processing is optimized based on both zero-forcing (ZF) and minimum mean-square-error (MMSE) criteria under relay power constraints. Various transmit and receive beamforming methods are compared including eigen beamforming, antenna selection, random beamforming, and modified equal gain beamforming. Local and global power control methods are designed to achieve fairness among all users and to maximize the system signal-to-noise ratio (SNR). Numerical results show that the proposed multiuser two-way relay processing can efficiently eliminate both co-channel interference (CCI) and self-interference (SI).

MIMO Radar Using Compressive Sampling

Abstract: A multiple-input multiple-output (MIMO) radar system is proposed for obtaining angle and Doppler information on potential targets. Transmitters and receivers are nodes of a small scale wireless network and are assumed to be randomly scattered on a disk. The transmit nodes transmit uncorrelated waveforms. Each receive node applies compressive sampling to the received signal to obtain a small number of samples, which the node subsequently forwards to a fusion center. Assuming that the targets are sparsely located in the angle-Doppler space, based on the samples forwarded by the receive nodes the fusion center formulates an l 1 -optimization problem, the solution of which yields target angle and Doppler information. The proposed approach achieves the superior resolution of MIMO radar with far fewer samples than required by other approaches. This implies power savings during the communication phase between the receive nodes and the fusion center. Performance in the presence of a jammer is analyzed for the case of slowly moving targets. Issues related to forming the basis matrix that spans the angle-Doppler space, and for selecting a grid for that space are discussed. Extensive simulation results are provided to demonstrate the performance of the proposed approach at difference jammer and noise levels.

Tensor Algebra and Multidimensional Harmonic Retrieval in Signal Processing for MIMO Radar

Abstract: Detection and estimation problems in multiple-input multiple-output (MIMO) radar have recently drawn considerable interest in the signal processing community. Radar has long been a staple of signal processing, and MIMO radar presents challenges and opportunities in adapting classical radar imaging tools and developing new ones. Our aim in this article is to showcase the potential of tensor algebra and multidimensional harmonic retrieval (HR) in signal processing for MIMO radar. Tensor algebra and multidimensional HR are relatively mature topics, albeit still on the fringes of signal processing research. We show they are in fact central for target localization in a variety of pertinent MIMO radar scenarios. Tensor algebra naturally comes into play when the coherent processing interval comprises multiple pulses, or multiple transmit and receive subarrays are used (multistatic configuration). Multidimensional harmonic structure emerges for far-field uniform linear transmit/receive array configurations, also taking into account Doppler shift; and hybrid models arise in-between. This viewpoint opens the door for the application and further development of powerful algorithms and identifiability results for MIMO radar. Compared to the classical radar-imaging-based methods such as Capon or MUSIC, these algebraic techniques yield improved performance, especially for closely spaced targets, at modest complexity.

A Framework for Training-Based Estimation in Arbitrarily Correlated Rician MIMO Channels With Rician Disturbance

Abstract: In this paper, we create a framework for training-based channel estimation under different channel and interference statistics. The minimum mean square error (MMSE) estimator for channel matrix estimation in Rician fading multi-antenna systems is analyzed, and especially the design of mean square error (MSE) minimizing training sequences. By considering Kronecker-structured systems with a combination of noise and interference and arbitrary training sequence length, we collect and generalize several previous results in the framework. We clarify the conditions for achieving the optimal training sequence structure and show when the spatial training power allocation can be solved explicitly. We also prove that spatial correlation improves the estimation performance and establish how it determines the optimal training sequence length. The analytic results for Kronecker-structured systems are used to derive a heuristic training sequence under general unstructured statistics. The MMSE estimator of the squared Frobenius norm of the channel matrix is also derived and shown to provide far better gain estimates than other approaches. It is shown under which conditions training sequences that minimize the non-convex MSE can be derived explicitly or with low complexity. Numerical examples are used to evaluate the performance of the two estimators for different training sequences and system statistics. We also illustrate how the optimal length of the training sequence often can be shorter than the number of transmit antennas.

Cooperative MIMO channel models: A survey

Abstract: 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.

Coherent and Differential Space-Time Shift Keying: A Dispersion Matrix Approach

Abstract: Motivated by the recent concept of Spatial Modulation (SM), we propose a novel Space-Time Shift Keying (STSK) modulation scheme for Multiple-Input Multiple-Output (MIMO) communication systems, where the concept of SM is extended to include both the space and time dimensions, in order to provide a general shift-keying framework. More specifically, in the proposed STSK scheme one out of Q dispersion matrices is activated during each transmitted block, which enables us to strike a flexible diversity and multiplexing tradeoff. This is achieved by optimizing both the space-time block duration as well as the number of the dispersion matrices in addition to the number of transmit and receive antennas. We will demonstrate that the resultant equivalent system model does not impose any Inter-Channel Interference (ICI), and hence the employment of single-stream Maximum Likelihood (ML) detection becomes realistic at a low-complexity. Furthermore, we propose a Differential STSK (DSTSK) scheme, assisted by the Cayley unitary transform, which does not require any Channel State Information (CSI) at the receiver. Here, the usual error-doubling, caused by the differential decoding, gives rise to 3-dB performance penalty in comparison to Coherent STSK (CSTSK). Additionally, we introduce an enhanced CSTSK scheme, which avoids the requirement of Inter-Antenna Synchronization (IAS) between the RF chains associated with the transmit Antenna Elements (AEs) by imposing a certain constraint on the dispersion matrix design, where each column of the dispersion matrices includes only a single non-zero component. Moreover, according to the turbo-coding principle, the proposed CSTSK and DSTSK schemes are combined with multiple serially concatenated codes and an iterative bit-to-symbol soft-demapper. More specifically, the associated STSK parameters are optimized with the aid of Extrinsic Information Transfer (EXIT) charts, for the sake of achieving a near-capacity performance.

Interference Alignment With Asymmetric Complex Signaling—Settling the Høst-Madsen–Nosratinia Conjecture

Abstract: It has been conjectured by Ho-Madsen and Nosratinia that complex Gaussian interference channels with constant channel coefficients have only one degree-of-freedom regardless of the number of users While several examples are known of constant channels that achieve more than 1 degree-of-freedom, these special cases only span a subset of measure zero In other words, for almost all channel coefficient values, it is not known if more than 1 degree-of-freedom is achievable In this paper, we settle the Host-Madsen-Nosratinia conjecture in the negative We show that at least 12 degrees-of-freedom are achievable for all values of complex channel coefficients except for a subset of measure zero For the class of linear beamforming and interference alignment schemes considered in this paper, it is also shown that 12 is the maximum number of degrees-of-freedom achievable on the complex Gaussian 3 user interference channel with constant channel coefficients, for almost all values of channel coefficients To establish the achievability of 12 degrees-of-freedom we use the novel idea of asymmetric complex signaling - ie, the inputs are chosen to be complex but not circularly symmetric It is shown that unlike Gaussian point-to-point, multiple-access and broadcast channels where circularly symmetric complex Gaussian inputs are optimal, for interference channels optimal inputs are in general asymmetric With asymmetric complex signaling, we also show that the 2 user complex Gaussian X channel with constant channel coefficients achieves the outer bound of 4/3 degrees-of-freedom, ie, the assumption of time-variations/frequency-selectivity used in prior work to establish the same result, is not needed

Cooperative Multi-Cell Block Diagonalization with Per-Base-Station Power Constraints

Abstract: Block diagonalization (BD) is a practical linear precoding technique that eliminates the inter-user interference in downlink multiuser multiple-input multiple-output (MIMO) systems. In this paper, we apply BD to the downlink transmission in a cooperative multi-cell MIMO system, where the signals from different base stations (BSs) to all the mobile stations (MSs) are jointly designed with the perfect knowledge of the downlink channels and transmit messages. Specifically, we study the optimal BD precoder design to maximize the weighted sum-rate of all the MSs subject to a set of per-BS power constraints. This design problem is formulated in an auxiliary MIMO broadcast channel (BC) with a set of transmit power constraints corresponding to those for individual BSs in the multi-cell system. By applying convex optimization techniques, this paper develops an efficient algorithm to solve this problem, and derives the closed-form expression for the optimal BD precoding matrix. It is revealed that the optimal BD precoding vectors for each MS in the per-BS power constraint case are in general non-orthogonal, which differs from the conventional orthogonal BD precoder design for the MIMO-BC under one single sum-power constraint. Moreover, for the special case of single-antenna BSs and MSs, the proposed solution reduces to the optimal zero-forcing beamforming (ZF-BF) precoder design for the weighted sum-rate maximization in the multiple-input single-output (MISO) BC with per-antenna power constraints. Suboptimal and low-complexity BD/ZF-BF precoding schemes are also presented, and their achievable rates are compared against those with the optimal schemes.

MIMO-OFDM for LTE, WiFi and WiMAX: Coherent versus Non-coherent and Cooperative Turbo Transceivers

Abstract: The MIMO capacity theoretically increases linearly with the number of transmit antennas, provided that the number of receive antennas is equal to the number of transmit antennas. With the further proviso that the total transmit power is increased proportionately to the number of transmit antennas, a linear capacity increase is achieved upon increasing the transmit power. However, under realistic conditions the theoretical MIMO-OFDM performance erodes and hence to circumvent this degradation, our monograph is dedicated to the design of practical coherent, non-coherent and cooperative MIMO-OFDM turbo-transceivers...