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Massive multiple-input-multiple-output (MIMO) systems use few hundred antennas to simultaneously serve large number of wireless broadband terminals. It has been incorporated into standards like long term evolution (LTE) and IEEE802.11 (Wi-Fi). Basically, the more the antennas, the better shall be the performance. Massive MIMO systems envision accurate beamforming and decoding with simpler and possibly linear algorithms. However, efficient signal processing techniques have to be used at both ends to overcome the signaling overhead complexity. There are few fundamental issues about massive MIMO networks that need to be better understood before their successful deployment. In this paper, we present a detailed review of massive MIMO homogeneous, and heterogeneous systems, highlighting key system components, pros, cons, and research directions. In addition, we emphasize the advantage of employing millimeter wave (mmWave) frequency in the beamforming, and precoding operations in single, and multi-tier massive MIMO systems. Keywords: 5G wireless networks; massive MIMO; linear precoding; encoding; channel estimation; pilot contamination; beamforming; HetNets

It is well known that multiple-input multiple-output (MIMO) systems can provide very high spectral efficiencies in a rich scattering propagation medium Telatar (1999). They are hence a promising solution for high-speed, spectrally efficient, and reliable wireless communication Raoof et al. (2008) .When coherent signal detection is to be performed at the receiver, channel state information at the receiver (CSIR) is required, for which a channel estimation step is necessary. Channel estimation plays a critical role in the performance of the receiver. It is a real challenge in practical MIMO systems where the quality of data recovery is as important as attaining a high data throughput. In order to obtain the CSIR, usually some known training (also called pilot) symbols are sent from the transmitter, based on which the receiver estimates the channel before proceeding to the detection of data symbols. The classical approach consists in time-multiplexing pilot and data symbols, usually referred to as pilot symbol-assisted modulation (PSAM) Cavers (1991). We start the chapter by introducing the PSAM channel estimation for MIMO systems (Section 2). Instead of this classical channel estimation based on pilot symbols only, we can perform semi-blind estimation that in addition to pilot symbols, makes use of data symbols in channel estimation. In this way, a considerable performance improvement can be achieved at the price of increased receiver complexity De Carvalho & Slock (1997); Giannakis et al. (2001); Sadough (2008). Usually, these semi-blind approaches are implemented in an iterative scheme when channel coding is performed. That is, channel estimation is performed iteratively together with signal detection and channel decoding Sadough, Ichir, Duhamel & Jaffrot (2009). We, hence, continue Section 2 by considering semi-blind estimation for the case of timemultiplexed pilots. The drawback of the PSAM scheme is the encountered loss in the spectral efficiency by the periodic insertion of pilot symbols. As an alternative to this method, overlay pilots (OP) can be employed, where pilot symbols are sent in parallel with data symbols Hoeher & Tufvesson (1999). We introduce the OP approach in Section 3 and explain, in particular, pilot-only-based 6

The use of multiple antennas at both transmission and reception, also known as Multiple Input Multiple Output (MIMO) transmission systems, has received a lot of interest from the wireless communications industry during the last years. Communications in wireless channels using MIMO technologies exhibits a superior performance in terms of spectral efficiency, reliability and data rate when compared to conventional single antenna technologies (Foschini & Gans, 1998; Telatar, 1999). Existing and emerging standards for wireless communications such as IEEE 802.11 (WiFI), IEEE 802.16 (WiMAX) and Long Term Evolution (LTE), support multi-antenna transmission in their highest performance profiles. In spite of their potential performance-enhancing capabilities, most of the research on MIMO technologies up to the moment is based on theoretical studies. Typically, the expected gains of MIMO technologies are only shown under ideal conditions since most analysis rely on simulations. Experiments in real-world scenarios by means of hardware implementations are necessary to measure the actual performance of multi-antenna transmission methods. Hardware implementations not only take into account the real multipath propagation in wireless channels but also the implementation impairments so often ignored during the simulations. Hardware implementations can be split into three groups (Rupp et al., 2006). The first one is constituted by demonstrators which are frequently designed having in mind a particular standard or specification. Demonstrators usually exhibit good technical features for real-time implementations but they are extremely expensive and present poor flexibility and modularity. The second group is formed by prototypes of a final product. A prototype is a real-time implementation of a system specifically developed to support an industrial need. Prototypes often constitute a preliminary stage where the system is implemented and debugged and later on implemented as a consumer product. Finally, the third set is formed by testbeds that support real-time transmission capabilities while data is generated and post-processed off-line. In addition, hybrid solutions can be devised. As an example, a testbed can carry out some operations in real-time with the purpose of speeding up the measurement process. Usually, candidate signal processing operations to be implemented in real-time are those that operate at sample level and/or do common tasks for all experiments, i.e. I/Q modulation, up-sampling, pulse-shaped filtering, etc. Throughout this chapter we will focus on testbeds because they use open designs and are more often found in public research centres and academia. Various MIMO testbeds have been reported in the literature (Borkowski et al., 2006; Caban et al., 2006; Fabregas et al., 2006; Haustein et al., 2006; Nieto et al., 2006; Ramirez et al., 2008; 5

Environmental regulations demand efficient and eco-friendly ways of power generation. Coal continues to play a vital role in power generation because of its availability in abundance. Power generation using coal leads to local pollution problems. Hence this conflicting situation demands a new technology - Integrated Gasification Combined Cycle (IGCC). Gasifier is one of the subsystems in IGCC. It is a multivariable system with four inputs and four outputs with higher degree of cross coupling between the input and output variables. ALSTOM – a multinational and Original Equipment Manufacturer (OEM) - developed a detailed nonlinear mathematical model, validated made this model available to the academic community and demanded different control strategies which will satisfy certain stringent performance criteria during specified disturbances. These demands of ALSTOM are well known as “ALSTOM Benchmark Challenges”. The chapter is addressed to solve Alstom Benchmark Challenges using Proportional-Integral-Derivative-Filter (PIDF) controllers optimised by Genetic Algorithm.

This paper considers a multi-hop amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay network. In the multi-hop AF MIMO relay network, the performance deteriorates as the number of hops increases because the effect of noise is enhanced. To suppress the effect of noise, this paper proposes the two beamforming schemes using channel state information (CSI) for the transmit beamforming at the source, relay beamforming at the relay, and receive beamforming at the destination. The forward-and-backward-CSI based beamforming and all-CSI based beamforming schemes are designed at each node based on the minimum mean square error criterion under the source and relay transmit power constraint. The forward-and-backward-CSI based beamforming scheme is designed by using the two matrices, forward channel, and backward channel. The two matrices are designed by using the beamforming matrices and channels from the previous nodes. Unlike the forward-and-backward-CSI based beamforming scheme, the all-CSI based beamforming scheme is designed by using all channels and an iterative algorithm. In terms of the complexity, the forward-and-backward-CSI based beamforming scheme is superior to the all-CSI based beamforming scheme. However, the all-CSI based beamforming scheme has advantage over the forward-and-backward-CSI based beamforming scheme in terms of the performance.

High-order sliding-mode (HOSM) control is called quasi-continuous (QC), if it remains continuous everywhere except the HOSM set, where the sliding variables and their derivatives vanish. Such sliding-mode (SM) control features less chattering. Homogeneous QC SM control is designed for the general uncertain multi-input multi-output case and provides any predefined control smoothness level outside of the HOSM set.

Emerging wireless communication systems will be characterized by a tight coupling between communication and positioning. This is particularly apparent in millimeter-wave (mm-wave) communications, where devices use a large number of antennas and the propagation is well described by geometric channel models. For mm-wave communications, initial access, consisting in the beam selection and alignment of two devices, is challenging and time-consuming in the absence of location information. Conversely, accurate positioning relies on high-quality communication links with proper beam alignment. This paper studies this interaction and proposes a new position-aided beam selection protocol, which considers the problem of joint communication and positioning in scenarios with direct line-of-sight and scattering. Simulation results show significant reductions in latency with respect to a standard protocol., Comment: 10 pages, 5 figures, journal. Submitted to IEEE Transactions on Wireless Communications

Massive multiple-input multiple-output (MIMO) systems, which utilize a large number of antennas at the base station, are expected to enhance network throughput by enabling improved multiuser MIMO techniques. To deploy many antennas in reasonable form factors, base stations are expected to employ antenna arrays in both horizontal and vertical dimensions, which is known as full-dimension (FD) MIMO. The most popular two-dimensional array is the uniform planar array (UPA), where antennas are placed in a grid pattern. To exploit the full benefit of massive MIMO in frequency division duplexing (FDD), the downlink channel state information (CSI) should be estimated, quantized, and fed back from the receiver to the transmitter. However, it is difficult to accurately quantize the channel in a computationally efficient manner due to the high dimensionality of the massive MIMO channel. In this paper, we develop both narrowband and wideband CSI quantizers for FD-MIMO taking the properties of realistic channels and the UPA into consideration. To improve quantization quality, we focus on not only quantizing dominant radio paths in the channel, but also combining the quantized beams. We also develop a hierarchical beam search approach, which scans both vertical and horizontal domains jointly with moderate computational complexity. Numerical simulations verify that the performance of the proposed quantizers is better than that of previous CSI quantization techniques., Comment: 15 pages, 6 figures

Consider a massive multiple-input multiple-output (MIMO) system, where the base station employing space-division multiple access simultaneously transmits information and energy to the information and energy users, respectively. The objective is to maximize the energy harvesting utility of the energy users, while guaranteeing the outage probability requirements of the information users. Since conventional beamformers, such as the maximum ratio transmission (MRT) and zero-forcing (ZF) beamformers, are designed for information transmission, a hybrid beamformer is first proposed to improve both the spectral efficiency (SE) of the information users and the harvested power (HP) of the energy users. Then, based on the analysis of SE and HP, the utility maximization problem is formulated and solved, followed by the proposal of a power allocation scheme for the hybrid information and energy transfer system. Theoretical and simulated results are presented to show that the hybrid beamformer is able to improve the SE-HP trade-off in comparison to the MRT and ZF beamformers, and gives the best energy harvesting utility at the expense of moderate complexity.

Recently the combination of massive multiple-input multiple-output (MIMO) and spatial modulation (SM), has been considered as a promising concept for uplink transmission, in which each user equipment (UE) uses SM for uplink transmission and base station (BS) is equipped with massive antennas. In this paper, we evaluate a massive single-carrier (SC) SM-MIMO system with frequency domain equalization, where SC transmission is combined with SM (SC-SM) to combat the negative impact of broadband frequency-selective fading, and frequency domain equalization is utilized to mitigate the intersymbol-interference with a low complexity. With frequency domain processing, a framework is proposed to analyze the achievable uplink spectral efficiency (SE) of single-cell massive SC-SM MIMO systems. Based on this framework, the closed-form SE lower bound of frequency domain maximum ratio combining is derived, and both the derivation of framework and SE lower bound are much more complicated than those of systems with time domain combining. Monte Carlo simulations verify the tightness of proposed SE lower bound, and show that massive SC-SM MIMO systems can outperform the SE of conventional single transmit antenna (TA) massive MIMO systems. The systems can even have a better SE performance than massive MIMO systems with spatial multiplexing UEs in a low signal-to-noise ratio. Finally, the SE gain is found to be mainly dependent on the specific number of UE's TAs, which facilitates an SE maximization via optimizing the number of TAs.

In this letter, we propose a novel pilot assignment scheme for the pilot contamination problem in massive multiple-input multiple-output multi-cell networks. Based on the asymptotic signal-to-interference-plus-noise ratio (SINR), the proposed pilot assignment scheme adopts the harmonic SINR utility function to quantify the fairness of all users in the network. Specifically, we formulate the pilot assignment problem as a minimum-weight multi-index assignment problem. For a two-cell network, this problem can be solved by the Hungarian algorithm with a strongly polynomial complexity. For the general multi-cell networks with more than two cells, this problem is in general NP-hard and we propose an efficient algorithm to obtain a suboptimal solution. The numerical experiments show that the proposed algorithms outperform other conventional pilot assignment schemes.

Multiple-input multiple-output (MIMO) radars have attracted much attention for their superior ability to enhance a system's performance. In this study, the authors' goal was the study of the spatial multiplexing gain of MIMO radars with widely separated antennas (WS-MIMO), which the authors showed that is equal to the number of unambiguously detectable targets. They obtained this number from two different aspects: first, by defining the ambiguity function of a WS-MIMO radar in the case of multiple targets, suitable for such purpose; Second, by modelling the MIMO radar system with a MIMO wireless channel. They showed that a MIMO radar is indeed a MIMO wireless system communicating the information about the existence of the targets. By such modelling, they could easily make the relation between dual concepts of MIMO radar and MIMO communication, one of which is the multiplexing gain.

In this paper, a variety of layered relay-and-antenna selection (LRAS) strategies are developed for the two-way multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying systems in the presence of spatial correlation between antennas over fading channels. On the basis of the achievable sum-rate (ASR) maximization, the condition number (CN), adaptive discrete stochastic approximation (A-DSA), Gram–Schmidt (GS), and squared Frobenius norm (SFN)-based LRAS algorithms are investigated under an equal power allocation. To reduce the computational complexity of the relay-and-antenna selection (RAS) selection strategies, the best single relay and the subset of transmit-and-receive (Tx/Rx) antenna pairs are selected and separated into a two-stage manner. Remarkably, the LRAS techniques enable to alleviate substantially the computational complexity incurred by an exhaustive-mode RAS search algorithm. Finally, simulation results demonstrate the excellent sum-rate capacity of the proposed LRAS methods over other existing selection ones for MIMO two-way multiple-AF-relay systems.

In this paper, we study the performance of the training based two-step channel estimation in two-way multiple-input multiple-output relay systems over Rayleigh channels. We first estimate the forward channel during the first phase. During the second phase for the composite channel estimation, singular value decomposition based maximum likelihood method is applied in two way relay systems, which is extended from one way relay systems. Hence, the backward channel is estimated with the given forward channel and composite channel. In general, the proposed estimation scheme can also be extended from the system with a single relay antenna to multiple relay antennas. Moreover, we derive the proposed training sequences and relay gain that aim to minimizes the trace of the approximate Bayesian Cramer–Rao lower bound with respect to the individual channels. The numerical results are shown that although the training sequence is designed to improve individual channel mean square error performance, it can also improve composite channel estimator performance.

Massive MIMO is a promising next-generation wireless access technology. By flexibly assigning different numbers of antennas among connections, the transmission rate can be adjusted according to user requirement and channel conditions. However, providing scalable-video-encoded (SVC) multimedia streams with such a technology is challenging because this cross-layer issue involves each user's allocated antennas as well as the assigned layers. In this paper, we propose a cross-layer scheme called Utility-Based Layer and Antenna Allocation (UB-LAA). Given each base station's available antennas and each user's channel conditions as well as their subscribed SVC stream, UB-LAA decides each layer's serving base station and transmitting antennas to maximize the system's total utility. Through analysis, we prove that this allocation problem is NP-complete, and our polynomial-time heuristic provides a bounded performance difference to the optimum solution. Simulation results indicated that, under various circumstances, UB-LAA flexibly allocates resources to reflect user requirements and channel conditions, and has a performance that is approximate to the optimal solution.

In this letter, we investigate robust beamforming design problem in downlink multiple-input-multiple-output non-orthogonal multiple access networks considering worst-case channel uncertainties, where worst-case means the channel uncertainties among all of them provide us the worst system performance. We propose to solve the problem using cutting-set method. The proposed cutting-set method consists of alternating optimization and pessimization steps. In the optimization step, we maximize the worst-case achievable rate of a user under worst-case achievable rate constraints of other users given finite subset of channel uncertainties. In the pessimization step, we determine the worst-case channel uncertainties. It is shown through simulation results that our proposed robust design is superior to non-robust one.

In this brief, we present a virtual channel (VC) optimization approach for overloaded multiple-input multiple-output (MIMO) systems. With this approach, a VC vector is generated at the transmitter, which is combined with the actual wireless channel matrix to form the overall transmission channel matrix. Through VC optimization, the overall transmission channels can be properly adjusted in favor of the signal detection, leading to an improved performance. Moreover, we investigate the overloaded MIMO system in which the number of receive antennas equals the number of transmit antennas. By using superposition VC method, this overloaded MIMO system allows more number of data streams to be transmitted than the number of transmit antennas. The methods for obtaining the optimal VC vector are presented. Simulation results illustrate the effectiveness of the proposed approaches.

This paper investigates secure cooperative transmissions in a dual-hop MIMO relay system using a combined transmit antenna selection (TAS) and maximal-ratio combining (MRC) scheme over the Nakagami- $m$ fading channels, where an adaptive decode-and-forward relaying protocol and an multi-antenna eavesdropper are considered. Due to the feedback delay, channel state information (CSI) for TAS might be outdated at both the source and the relay. To evaluate the secrecy performance of the TAS/MRC scheme and the impacts of outdated CSI, the closed-form expressions for the metrics of exact ergodic secrecy rate and exact secrecy outage probability are derived under both perfect and outdated CSI conditions in a channel feedback error model. In order to explicitly reveal the behaviors of the secrecy performance in high signal-to-noise ratio regime, asymptotic expressions for both the metrics are further derived. As validated by simulation results, analytically numerical results demonstrate that outdated the CSI always results in a loss in the secrecy performance, but the loss can be recovered by increasing the number of antennas at legitimate receivers. Furthermore, the outdated CSI yields a reduced secrecy diversity order, whereas only the perfect CSI leads to the full secrecy diversity order.

This letter proposes an aggregation-assisted combining (AAC) for multiple-input multiple-output multiple automatic repeat request systems. The proposed AAC can be considered as a hybrid scheme of the symbol-level combining (SLC) and bit-level combining (BLC), which consists of the aggregation-assisted log-likelihood ratio (LLR) calculation and subsequent LLR combining stages. The aggregation-assisted LLR calculation stage is performed in a similar manner on the SLC except that the interference-to-noise reformulation is performed instead of the terminated-packet elimination; thus, the remaining interference from the terminated packets is regarded as additional noise. This additional noise can degrade the LLR quality from the aggregation-assisted LLR calculation stage. Therefore, the proposed AAC combines the currently calculated LLRs with the previously calculated LLRs similar to the BLC when the previously calculated LLRs have less LLR contaminations, i.e., they experience fewer numbers of terminated packets. The simulation results verify that the proposed AAC outperforms the BLC and even achieves a performance comparable with the SLC with simplified reception procedures.

In this letter, we propose a space-time transmission scheme (STTS) for large multiple-input multiple-output (MIMO) communication systems. These systems are primarily used to transmit a huge amount of data. The existing space-time block codes (STBCs) are not suitable for these systems due to the fact that these STBCs require very large channel coherence time (more than the number of transmit antennas), render poor data rate (less than one), and aim at full spatial diversity. In a practical large MIMO system with one thousand transmit and one thousand receive antennas, the diversity order of ${10}^{{6}}$ can be achieved; however, such a high value of diversity order is not required in practical systems. Therefore, an STTS with good data rate, parsimoniously utilized temporal dimensions, and symbol-wise decoding is essentially required for practical large MIMO systems. In this letter, we emphasize design of a new STTS by relaxing the constraint of achieving full spatial diversity. In the proposed STTS, the data rate of the large MIMO system is increased at the expense of the reduction in spatial diversity order. An approximate expression of symbol error rate of the proposed system is obtained-based on the moment generating function of the instantaneous received signal-to-noise ratio. Further, it is shown that the diversity order of the proposed STTS-based system is one less than the number of receive antennas.

In this paper, we investigate the dynamic small cell (SC) clustering strategy and their precoding design problem for interference coordination in two-tier heterogeneous networks (HetNets) with massive MIMO (mMIMO). To reduce interference among different SCs, an interference graph-based dynamic SC clustering scheme is proposed. Based on this, we formulate an optimization problem as design precoding weights at macro base station (MBS) and clustered SCs for maximizing the downlink sum rate of SC users (SUs) subject to the power constraint of each SC BS (SBS), while mitigating inter-cluster, eliminating inter-tier, intra-cluster and multi-macro user (MU) interference. To eliminate the inter-tier and multi-MU interference simultaneously, we propose a clustered SC block diagonalization precoding scheme for the MBS. Next, each SU’s precoding vector at clustered SCs is designed as the product of the following two parts. The first part is designed with singular value decomposition to remove the intra-cluster interference. The second part is designed to coordinate the inter-cluster interference for maximizing the downlink sum rate of SUs, which is a non-convex optimization problem and difficult to solve directly. A non-cooperative game-based distributed algorithm is proposed to obtain a suboptimal solution. Meanwhile, we prove the existence and uniqueness of Nash equilibrium for the formed game. Finally, simulation results verify the effectiveness of our proposed schemes.

This paper considers the uplink of multiuser massive multi-input multi-output systems with a mixed analog-to-digital converter (ADC) architecture, in which the base station (BS) is equipped with ADCs of different resolution levels. While higher resolution, ADCs reduce the quantization error to improve the performance; they also incur higher energy. This paper studies the receive energy efficiency (EE) and the ADC resolution profile design under the maximum-ratio combining receiver. First, closed-form approximations for the spectral efficiency (SE) and receive EE are derived for a general mixed ADC structure. Then, the ADC resolution profile optimization problem that maximizes the receive EE with respect to SE requirement is formulated. An algorithm based on decremental searching and dynamic programming is proposed whose complexity is linear in the number of BS antennas. Numerical results verify that with the proposed design, the mixed-ADC receiver can have nearly the same SE performance as the all full-resolution one but with considerably lighter burden of energy consumption.

Massive multiple-input multiple-output (MIMO) technology employs hundreds of antennas at the base station (BS) of a cellular system. Activating hundreds of antennas requires hundreds of radio-frequency (RF) chains that lead to high cost and high energy consumption. Antenna selection techniques reduce the number of RF chains while curtailing the resulting performance loss. In this study, the authors consider massive-MIMO downlink with zero-forcing (ZF) precoding in a single cell. In ZF precoding with antenna selection, the number of users must always be less than or equal to the number of selected antennas, which may require adopting user selection (scheduling) algorithms. They propose a joint user and antenna selection algorithm to increase BS's energy efficiency (EE) and show that its performance is very close to that of the optimum exhaustive-search based scheme. Using an analytical approximation for EE of the proposed scheme in asymptotically large numbers of users region, they find the optimum number of antennas to be selected.

The deluge of huge data demanding applications has imposed a challenge for next generation cellular system to support high data rate with reduced energy consumption besides ensuring good quality of service. Massive MIMO and small cells are the foremost technologies to address such challenges. Massive MIMO technique refers to deploying a very large number of antennas at the base station, and thus, improving energy efficiency and spectral efficiency of wireless networks. Small cell provides high data rate and good coverage with reduced transmit power by decreasing the distance between base station and user. This paper surveys state of the art of massive MIMO technique with small cell network. First, we discuss fundamental background for massive MIMO. Then, performance metrics and modeling tools for system analysis are studied. Next, details of enabling technologies to massive MIMO small cell network are stated in the paper. Finally, the paper highlights future challenges and research problems.

We consider a full duplex (FD) multiple-input multiple-output (MIMO) underlay cognitive radio cellular network, in which an FD secondary base-station (BS) serves multiple half-duplex uplink (UL) and downlink secondary users (SUs) at the same time and frequency. We assume that the channel state information (CSI) available at the transmitters is imperfect, and the errors of the CSI are assumed to be norm bounded. Under the impact of channel uncertainty, we address the sum mean-squared-errors minimization problem subject to individual power constraints at the UL SUs, a total power-constraint at the secondary BS, and the interference constraints on the primary users by the secondary network. By transforming the problem into an equivalent semidefinite programming (SDP), we propose an iterative alternating algorithm to compute the transceiver matrices jointly. Moreover, to reduce the high computational complexity of the SDP method, we develop a cutting-set method, which solves the problem by alternating between an optimization step (transceiver design) and a pessimization step (worst-case channel analysis). Numerical results are presented to show the effectiveness and robustness of the proposed algorithms.

A dual-band multiple-input multiple-output (MIMO) antenna is presented. The proposed MIMO antenna consists of two elements of meander-line antenna with an isolation improvement structure located between the two radiating antenna elements. The antennas operate in the 4G long-term evolution (LTE) (699-798 MHz) band, and Universal Mobile Telecommunications Service (UMTS) (Digital Cellular System (DCS)/Personal Communications Service (PCS)) bands (1920-2170 MHz) with | S 11 | = -6 dB (voltage standing wave ratio (VSWR) = 3) matching criteria. The measured mutual coupling is lower than -15 and -22 dB at the LTE 700 bands, and UMTS bands, respectively. The diversity performance of the envelope correlation coefficient and the mean effective gain meets the diversity criteria for mobile communications. Total radiation efficiencies range between 60 and 90% over the operating frequency bands. A prototype antenna was fabricated and tested for design verification. The simulated results are in good agreement with the measurements.

Motivated by recent developments in time-division duplex massive multiple-input multiple-output (MIMO) systems, this paper investigates semi-blind channel estimation for multiuser MIMO systems. An expectation-maximization (EM) algorithm is derived for semi-blind channel estimation and a tractable EM algorithm is obtained by assuming a Gaussian distribution for the unknown data symbols, which improves channel estimates even when the data symbols are drawn from a finite constellation, such as quadrature phase-shift keying. An alternate EM algorithm is also derived by employing suitable priors on the channel coefficients and it is shown to outperform the EM algorithm with no priors in the low signal-to-noise ratio regime. To analytically understand the performance of the semi-blind scheme, Cramer–Rao bounds (CRBs) for semi-blind channel estimation are derived for deterministic and stochastic (Gaussian) data symbol models. To get insight into the behavior of a massive MIMO system, the asymptotic behavior of the CRBs as the number of antennas at the base station grows is analyzed. The numerical results show the benefits of semi-blind estimation algorithm as measured by the mean squared error. In particular, the performance of the EM algorithm becomes closer to the genie-aided maximum likelihood estimator based on known data symbols as the number of antennas increases. This result is consistent with the asymptotic analysis of the two CRBs indicating that semi-blind channel estimation for massive MIMO systems is very promising.

Space division multiplexing (SDM) transmission technology is the prime candidate for next technological breakthrough in fiber-optic communication systems, as spatially structured multicore fibers and multimode fibers allow exploitation of the spatial degrees of freedom. Although the use of multi-input multi-output (MIMO) signal processing has significantly contributed to the development of MIMO-SDM transmission, differential mode delay (DMD) and mode dependent loss (MDL) remain as restricting factors of long-haul MIMO-SDM transmission. This paper starts by reviewing the recent progress demonstrated by SDM transmission experiments. Issues with MIMO-SDM transmission including DMD and MDL are then discussed with their methodologies based on optical and digital approaches. Next, brief descriptions of linear and nonlinear MIMO signal processing techniques that enable robust and reliable MIMO-SDM transmission are provided with complexity and performance comparisons, followed by a discussion of their adaptation in coherent MIMO-SDM transmission. We also elucidate the experimental evaluation of frequency selective channels in a multicore few-mode fiber with experimental evaluations, and discuss their impact on MIMO-SDM signal transmission from a signal processing perspective.

In this paper, a novel protocol is proposed in which mobile terminals (MT) form a virtual Multiple-input Multiple-output (MIMO) uplink by means of device relaying on Device to Device (D2D) tier in 5G Cellular Network. The competitive scenario is considered in which each of the selfish MTs tries to transmit its own data and not relay others’ data in the formed virtual MIMO. The main focus is to design an incentive for MTs to form the virtual MIMO and cooperate in relaying others data. A direct revelation on-line mechanism for the BS is designed, in order to assist forming a stable virtual MIMO. A self-punishment mechanism is also proposed in which MTs autonomously punish malicious MTs that do not cooperate in relaying. We prove that our designed direct revelation on-line mechanism and proposed self-punishment mechanism enforce all-cooperation (all-C) profile as a Nash equilibrium (NE), under uncertainty in the presence of MTs in the formed virtual MIMO. Our simulation results confirm that the proposed protocol, even in the competitive scenario, increases the bit rate and decreases power consumption at the same time. The proposed protocol can improve the energy efficiency up to 35 percent compared to a non-cooperative case, i.e., Single-Input Multiple-Output (SIMO) uplink. Moreover, if the multi-user MIMO transmission is used for the uplink medium access layer, the proposed protocol can improve the energy efficiency up to 42 percent compared to SIMO uplink with multi-user MIMO transmission. Under the proposed OCVM protocol with Shapley value fairness, the price of anarchy reaches to 0.78 in the competitive scenario. In addition, the energy efficiency improvement of our proposed protocol is almost robust to the preferences of MTs. Simulation results show that if BS employs our on-line mechanism and MTs autonomously punish malicious MTs, the malicious MTs cannot gain by defecting from relaying other MTs’ data.

By leveraging the natural multipath propagation of electromagnetic waves, waveforming is proposed as a promising paradigm that treats each multipath component in a wireless channel as a virtual antenna to exploit the spatial diversity. As the most commonly known waveforming technique for wideband systems, the time-reversal (TR) signal transmission produces a TR resonance by coherently combining multipath energy distributed on virtual antennas, and thus boosts the received signal strength while reducing interference. The wideband waveforming is, in many ways, similar to the multiple-input multiple-output (MIMO) beamforming, where multiple antennas are deployed to imitate a multipath transmission when the bandwidth is limited. In this paper, we provide an overview of recent advances on the wideband waveforming, including massive multipath effect, optimal resource allocation, wireless power transfer and secrecy enhancement for secured communications, and compare with the corresponding counterparts of traditional MIMO beamforming.

This paper first investigates an $M$ -by-2 massive multiple-input multiple-output (MIMO) system that transmits a single stream is investigated. For this system, we propose a space-time line code (STLC), which is a transmitting and combining (at a receiver) scheme that achieves full spatial diversity. For the STLC, two consecutive ( time ) information symbols are weighted as per channel gains ( space ), combined at each transmit antenna, and transmitted through the $M$ transmit antennas for two consecutive symbol times. With two receive antennas, the STLC receiver simply combines the signals received in the two symbol times and achieves a diversity order of $2M$ (full diversity). We show that the proposed STLC asymptotically achieves the maximum (optimal) received signal-to-noise ratio as $M$ increases with significantly reduced computational complexity compared with the optimal scheme. Because the proposed STLC receiver requires no or partial channel state information, it avoids the issue of massive MIMO channel estimation. Furthermore, the rigorous performance evaluation under spatially correlated and uncertain channel conditions reveals that the proposed STLC achieves comparable or better performance than the existing schemes, and the results verify that the proposed STLC scheme is a potential candidate for $M$ -by-2 massive MIMO systems. Next, the transmit antenna allocation algorithms are devised for a multiuser STLC system. Each user achieves full diversity order from the corresponding MIMO channels after the antenna allocation. The signal-to-interference-plus-noise ratio (SINR) of each user is analyzed considering the multiuser interference and channel uncertainty, and its lower bound is derived. Using the SINR lower bound, greedy algorithms that allocate the transmit antennas are devised. Rigorous simulation demonstrates that multiuser STLC with the proposed antenna allocation is robust against channel uncertainty and can improve the average SINR, improving the quality of experience. Furthermore, it is observed that the proposed STLC with antenna allocation method achieves the best performance if $M$ is sufficiently large. The results in this paper show that the STLC can be a potential candidate for an $M$ -by-2 (multiuser) massive MIMO systems.

In this letter, an integrated multiple-input–multiple-output (MIMO) antenna system is presented. The proposed design consists of a two-element printed inverted F-shape (IFA) MIMO antenna integrated with a two-element frequency-agile annular slot-based MIMO antenna system. The IFA operates at the WLAN band, while the annular slots act as an isolation enhancement structure between the two IFA elements. Furthermore, the annular slots are tuned over the bands from 1.73 to 2.28 GHz with a minimum bandwidth of 60 MHz. The slots are made reconfigurable using varactor diodes. The integrated MIMO antenna system is designed on commercially available FR-4 substrate with dimensions $\text{50} \times \text{110} \times \text{1.56}\,\text{mm}^{3}$ . All the antenna elements are of small size, low profile, and planar in structure and hence can easily be accommodated in wireless devices for second-generation cognitive radio applications.

This paper reports on a field trial in a robotic manufacturing cell. Channel measurements and transmission experiments were conducted, assisting the development of a light-emitting diode-based optical wireless communication (OWC) system tailored for the needs of industrial wireless applications. These are moderate data rates, reliability, and low latency. Since dedicated radio spectrum is hardly available, the usage of light is an interesting alternative. Due to its spatial confinement, OWC links provide enhanced security and are difficult to jam from outside a building—a particularly interesting property for industrial applications. We performed broadband distributed $8\times 6$ multiple-input multiple-output (MIMO) channel measurements in a manufacturing cell. Results confirm that the signal-to-noise ratio is sufficient if a line-of-sight (LOS) is available and bandwidth is limited to a few megahertz. However, small movements and rotations may lead to sudden fades of 10–20 dB, when an LOS is blocked. To improve reliability, antenna diversity concepts are applied. Results show that for reliable communication, MIMO diversity schemes are indispensable as it increases the probability of a free LOS significantly. Based on these insights, we suggest an OWC design tailored to industrial wireless applications.

This work targets a comprehensive understanding of the impact of the serial-relaying and multiple-input-multiple-output (MIMO) fading mitigation techniques on the performance of indoor power line communication (PLC) systems. While these techniques were studied extensively under additive Gaussian noise, we aim at highlighting the implications of Nakagami-like noise on the achievable performance levels. The author derive approximate closed-form expressions for the bit error rate (BER) under Rayleigh fading and Nakagami-m background noise where the obtained approximations are very close to the exact BERs. The derived expressions are useful for evaluating the achievable diversity orders and for relating the BER to the main parameters of the PLC system in a direct and intuitive way. In this context, we analytically prove that MIMO doubles the diversity order with different combining schemes while the diversity order of a system under Nakagami-like noise is only half the diversity order that would have been obtained under Gaussian noise. The author also shows that multi-hop relaying does not enhance the diversity order.

The high training cost of the massive multiple-input multiple-output (MIMO) systems motivates the use of hybrid digital/analog (HDA) beamforming structures. This paper considers the joint design of analog beamformers when both link ends of a millimeter (mm)-wave massive MIMO system are equipped with such HDA structures. We aim to maximize the multi-user MIMO net average throughput of the downlink in a frequency division duplex system. To achieve this, we develop an optimization framework, namely, user-centric virtual sectorization (UCVS), to explore the tradeoff of training overhead, beamforming gain, and spatial multiplexing gain. In the UCVS, both the channel-statistics-based analog beamforming design and a non-orthogonal downlink training scheme are investigated to reduce the necessary cost of instantaneous channel acquisition. By maximizing an approximate net average throughput, we devise efficient algorithms to realize the suboptimal UCVS. With generic mm-wave channel models, we demonstrate by simulations that our proposed scheme outperforms the state-of-the-art methods in various typical scenarios of mm-wave communications.

In this paper, we propose a numerically robust blind equalization scheme to mitigate cochannel and intersymbol interferences and separate signals from a convolutive mixture in multiple-input multiple-output (MIMO) communication systems. The robustness of the proposed scheme is achieved through a particular dual-mode operation applied to a constant-modulus-based space-time algorithm that corrects phase rotations. In the first mode of operation, the consistency in the nonlinear estimates of the transmitted signals is ensured. In the second mode, the Euclidean norms of the equalizer coefficient vectors decrease along the iterations, which allows the algorithm to return to the first mode of operation, where the estimation of the transmitted signals really occurs. In particular, we apply this scheme to a multimodulus version of the multiuser Shalvi-Weinstein algorithm (MU-SWA). By means of a deterministic stability analysis assuming the persistence of excitation condition, we show that the dual-mode MU-SWA does not diverge.

[EN] Multiple-input multiple-output (MIMO) radars have been shown to improve target detection for surveillance applications thanks to their proven high-performance properties. In this paper, the design, implementation, and results of a complete 3-D imaging frequency-modulated continuous-wave MIMO radar demonstrator are presented. The radar sensor working frequency range spans between 16 and 17 GHz, and the proposed solution is based on a 24-transmitter and 24-receiver MIMO radar architecture, implemented by timedivision multiplexing of the transmit signals. A modular approach based on conventional low-cost printed circuit boards is used for the transmit and receive systems. Using digital beamforming algorithms and radar processing techniques on the received signals, a high-resolution 3-D sensing of the range, azimuth, and elevation can be calculated. With the current antenna configuration, an angular resolution of 2.9° can be reached. Furthermore, by taking advantage of the 1-GHz bandwidth of the system, a range resolution of 0.5 m is achieved. The radio-frequency front-end, digital system and radar signal processing units are here presented. The medium-range surveillance potential and the high-resolution capabilities of the MIMO radar are proved with results in the form of radar images captured from the field measurements.

A low-profile dual-polarized high-isolation multiple input multiple output (MIMO) antenna array for wideband base-station applications is presented in this paper. The proposed dual-polarized antenna element has the advantage of lower profile ( $0.067\lambda $ ) by utilizing artificial magnetic conductor structure. The antenna array consisting of four elements is working within the frequency band from 2.4 to 3 GHz. Furthermore, decoupling branches among the elements are introduced to improve the isolation by about 10 dB. Both simulation and measured results indicate that the proposed dual-polarized antenna element has a good isolation over 28 dB. Moreover, the beamwidth of the antenna array can be effectively broadened by the adjustment of phase distributions of corresponding artificial material plane. Finally, a larger MIMO system is also investigated, and the simulation and measured results prove that dual-polarized dipole antenna MIMO array has good system performance.

This study focuses on robust Tomlinson–Harashima precoding transceiver design for multi-cell multiple-input–multiple-output interference channel with statistical channel state information error. The objective is formulated to minimise the maximum per-user mean square error (MSE) with per-transmitter power constraint. Since the problem is not jointly convex, an approximated method is proposed. The authors optimise the receiver matrix to be minimum MSE form as well as derive the optimisation problems of transmitter matrix and feedback matrix to be second-order cone programming, respectively. By use of the results, the three matrices are updated iteratively. The convergence of the proposed method is also proved. Simulation results show that the proposed scheme outperforms the robust linear transceiver in both MSE and bit error ratio.

Massive multiple input multiple output (MIMO) antenna systems have received a great deal of interest due to their applicability to industrial network systems. One of the major obstacles that reducing the performance of massive MIMO system is reference signal (RS) overhead which can be increased as the number of transmitter antenna increases in frequency division duplexing (FDD) system. Using channel reciprocity in time division duplexing (TDD) system can significantly increase the RS overhead performance using channel reciprocity. However, to use the channel reciprocity, channel calibration is a significant challenge to overcome in real system design. There are various base station (BS) calibration methods that have already successfully applied to the current BS, while there are few methods for the calibration of distributed user entities (UEs) and/or industrial Internet of things (IIoT) devices. In this paper, we propose a distributed UE RF calibration method of massive MIMO systems that uses the power headroom report. The power headroom is typically reported from the UEs and/or IIoT devices to the BS periodically or aperiodically. By including additional amplitude RF impairment information in the power headroom report, we can successfully transfer the necessary information from UE to BS. The proposed scheme does not require additional feedback, and is in compliance with current standards. There are five schemes based on the kind of information transferred to BS and the way of making a calibration factor that can be multiplied to the estimated channel. Numerical analysis shows that the proposed schemes can significantly increase the spectral efficiency with little system burden, and thus can be a core technology for the realization of massive MIMO for industrial network systems.

We design a jamming-resistant receiver scheme to enhance the robustness of a massive MIMO uplink system against jamming. We assume that a jammer attacks the system both in the pilot and data transmission phases. The key feature of the proposed scheme is that, in the pilot phase, we estimate not only the legitimate channel, but also the jamming channel by exploiting a purposely unused pilot sequence. The jamming channel estimate is used to constructed linear receive filters that reject the impact of the jamming signal. The performance of the proposed scheme is analytically evaluated using asymptotic properties of massive MIMO. The optimal regularized zero-forcing receiver and the optimal power allocation are also studied. Numerical results are provided to verify our analysis and show that the proposed scheme greatly improves the achievable rates, as compared to conventional receivers. Interestingly, the proposed scheme works particularly well under strong jamming attacks, since the improved estimate of the jamming channel outweighs the extra jamming power., submitted to IEEE Trans. Inf. Forensics and Security

This communication presents a planar ultra-wideband multi-input multi-output antenna with pattern diversity and isolation improvement based on the theory of characteristic modes. The proposed antenna (for new-generation wireless mobile terminals) consists of two ultra-wideband antenna elements—a compact quarter loop and a circular planar monopole located on the opposite edges of a rectangular ground plane. These two antenna elements are able to excite different modes in the ground plane and thus realize the desired diverse radiation patterns and high isolation without any additional decoupling structures. The experimental results show that both antenna elements are ultra-wideband with impedance bandwidths (return losses more than 6 dB for the quarter-loop antenna and more than 10 dB for the circular planar monopole antenna) of 130% (2–9.5 GHz). The isolation is over 20 dB with a peak value of 50 dB. The realized gains are above 1.5 dBi. The total efficiencies are above 70%. The envelope correlation coefficient is less than 0.03 assuming that the antenna operates in an isotropic channel.

Massive multiple-input-multiple-output (MIMO) is acknowledged as a key technology for the fifth generation of wireless communication systems, theoretically proved to be of higher throughput, better robustness, superior spectrum- and energy-efficiency with a general presumption that the channels tend to pairwise orthogonal with the increasing of the asymmetrical antenna pairs. Recently, more and more researches have cast light on massive MIMO system modelling. However, few investigations have been done on spatial characteristics of massive MIMO systems, especially the systems equipped with more than 100 antennas. This study focuses on the massive MIMO channel spatial characteristics based on indoor line-of-sight radio propagation measurement at 1.4725 GHz, and extracts spatial parameters such as angle of arrival, angle of departure and power azimuth spectrum from experimental data. The angles of departure (AODs) show a linear decrease along the linear antenna array, which are in agreement with the simulation of the ray tracing. On the basis of the realistic results of angular spread and the Gaussian density model, the investigation proves that antenna elements are deeply correlated and the envelope correlation coefficients show negative exponential down-trend with the increasing of antenna spacing in massive MIMO systems.

Preparing toward the new-generation communication by improving the capacity in the channel can be achieved by employing a MIMO system with polarization diversity means. This paper presents a low-profile $4 \times 4$ MIMO bidirectional antenna consisting of two composite antennas mounted on a ground plane. The composite antenna is constructed by stacking a notch antenna and a loop antenna on top of each other and each antenna is fed independently. This antenna is capable of dual-polarized radiation patterns pointing in two different directions, where the notch antenna produces a horizontally polarized wave in the ${x}$ -axis direction while the loop antenna gives a vertically polarized wave in the ${y}$ -axis direction. The combination of two composite antennas has good isolation between the elements and is capable of improving the channel capacity for indoor MIMO base station applications. This paper includes the validation of both the fabrication of the proposed antenna design and the channel propagation measurement using the proposed antenna, confirming the excellent antenna performance for long term evolution application at a frequency of 3.5 GHz.

A statistical beamforming (SBF) scheme based on the effective channel gain (ECG) is proposed for spatially correlated massive multiple-input multiple-output systems. The proposed SBF scheme consists of outer and inner precoders. The outer precoder is designed to eliminate multiuser interference based on the correlation matrix of downlink channel. Then, according to the ECG defined as the squared inner product of the dedicated channel and an arbitrary precoding vector, the inner precoder is selected among the eigenvectors of the dedicated channel’s correlation matrix with the maximum ECG. Simulation results show that the proposed SBF scheme outperforms conventional schemes.

A 12-port antenna array operating in the long term evolution (LTE) band 42 (3400–3600 MHz), LTE band 43 (3600–3800 MHz), and LTE band 46 (5150–5925 MHz) for 5G massive multiple-input multiple-output (MIMO) applications in mobile handsets is presented. The proposed MIMO antenna is composed of three different antenna element types, namely, inverted $\pi $ -shaped antenna, longer inverted L-shaped open slot antenna, and shorter inverted L-shaped open slot antenna. In total, eight antenna elements are used for the $8 \times 8$ MIMO in LTE bands 42/43, and six antenna elements are designed for the $6 \times 6$ MIMO in LTE band 46. The proposed antenna was simulated, and a prototype was fabricated and tested. The measured results show that the LTE bands 42/43/46 are satisfied with reflection coefficient better than −6 dB, isolation lower than −12 dB, and total efficiencies of higher than 40%. In addition to that, the proposed antenna array has also shown good MIMO performances with an envelope correlation coefficient lower than 0.15, and ergodic channel capacities higher than 34 and 26.5 b/s/Hz in the LTE bands 42/43 and LTE band 46, respectively. The hand phantom effects are also investigated, and the results show that the proposed antenna array can still exhibit good radiation and MIMO performances when operating under data mode and read mode conditions.

This paper investigates an issue of massive MIMO-based distributed detection that considers transceiver hardware impairments at both a massive-antenna fusion center (FC) and multiple single-antenna sensors. First, we derive closed-form expressions of the probability of detection and the probability of false alarm, and show that hardware impairments create finite ceilings on the achievable detection performance. Then, we formulate a constrained optimization problem as sum of linear ratios programming to maximize the detection probability. By exploiting the inherent problem structures, we further develop an algorithm based on the alternating direction method of multipliers. Extensive simulations demonstrate that the nonideal hardware has a fundamental impact on the distributed detection performance. More specifically, in the limit of an infinite number of antennas and infinite sensor reporting power budget, the effects of FC impairment and FC receiver noise vanish, while the sensor impairment dominates the achievable distributed detection performance.