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Due to the difficulty in manipulating the distribution of Wishart random matrices, the performance analysis of multiple-input-multiple-output (MIMO) channels has mainly focused on deriving capacity bounds via Jensen’s inequality. However, to the best of our knowledge, the tightness of Jensen’s bounds has not yet been rigorously quantified in the general MIMO context. This paper proposes a new methodology for measuring the tightness of Jensen’s bounds via the sandwich theorem. In particular, we first compare the tightness of two different pairs of upper/lower bounds for a general class of MIMO channels based on the unordered eigenvalue of the instantaneous correlation matrix and for arbitrary numbers of antennas. The tightness of Jensen’s bounds in different channel scenarios is investigated including multiuser MIMO with maximal ratio combining. Our analysis is facilitated by deriving some new results for finite-dimensional Wishart matrices, i.e., for the arbitrary moments of the unordered eigenvalue of central and non-central Wishart matrices. Our results provide very interesting insights into the implications of the system parameters, such as the number of antennas, and signal-to-noise ratio, on the tightness of Jensen’s bounds, and showcase the suitability and limitations of Jensen’s bounds. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the uplink of a single-cell multi-user single-input multiple-output (MU-SIMO) system with in-phase and quadrature-phase imbalance (IQI). In particular, we investigate the effect of receive (RX) IQI on the performance of MU-SIMO systems with large antenna arrays employing maximum-ratio combining receivers. In order to study how IQI affects channel estimation, we derive a new channel estimator for the IQI-impaired model and show that the higher the value of signal-to-noise ratio, the higher the impact of IQI on the spectral efficiency (SE). Moreover, a novel pilot-based joint estimator of the augmented multiple-input multiple-output (MIMO) channel matrix and IQI coefficients is described, and then, a low-complexity IQI compensation scheme is proposed, which is based on the IQI coefficients’ estimation and it is independent of the channel gain. The performance of the proposed compensation scheme is analytically evaluated by deriving a tractable approximation of the ergodic SE assuming transmission over Rayleigh fading channels with large-scale fading. Furthermore, we investigate how many mobile stations should be scheduled in massive MIMO systems with IQI and show that the highest SE loss occurs at the optimal operating point. Finally, by deriving asymptotic power scaling laws and proving that the SE loss due to IQI is asymptotically independent of the number of BS antennas, we show that massive MIMO is resilient to the effect of RX IQI. [ABSTRACT FROM AUTHOR]

This paper elaborates on the ergodic capacity of fixed-gain amplify-and-forward (AF) dual-hop systems, which have recently attracted considerable research and industry interest. In particular, two novel capacity bounds that allow for fast and efficient computation and apply for nonidentically distributed hops are derived. More importantly, they are generic since they apply to a wide range of popular fading channel models. Specifically, the proposed upper bound applies to Nakagami-m, Weibull, and generalized-K fading channels, whereas the proposed lower bound is more general and applies to Rician fading channels. Moreover, it is explicitly demonstrated that the proposed lower and upper bounds become asymptotically exact in the high signal-to-noise ratio (SNR) regime. Based on our analytical expressions and numerical results, we gain valuable insights into the impact of model parameters on the capacity of fixed-gain AF dual-hop relaying systems. [ABSTRACT FROM PUBLISHER]

We propose a stochastic model for multiple-input multiple- output (MIMO) communication systems based on the eigendecomposition of the spatial correlation matrix. It is shown that the channel matrix can be well modeled by the superposition of the spatial eigenmodes experiencing independent Nakagami-m fading. The proposed scheme is also compared with the existing correlation-based models using the data obtained from an indoor measurement campaign so that its performance is assessed in depth. [ABSTRACT FROM AUTHOR]

In Massive MIMO base stations (BSs), the hardware design needs to balance high spectral efficiency (SE) with low complexity. The level of hardware impairments (HWIs) indicates how strong the signal distortion introduced by hardware imperfections is. In particular, the analog-to-digital converters (ADCs) have an important impact on signal distortion and power consumption. This article addresses the fundamental problem of selecting the optimal hardware quality in the Massive MIMO space. In particular, we examine the optimal HWI and ADC bit allocation per BS antenna to maximize the SE. The results show that in co-located arrays with low channel gain variations across antennas, equal ADC bit allocation is optimal. In contrast, cell-free Massive MIMO systems benefit the most from optimizing the ADC bit allocation achieving improvements in the order of 2 [bit-per-channel-use] per user equipment when using regularized zero-forcing (RZF). In addition, when including the impact of power consumption in cell-free Massive MIMO with RZF, allocating low values of mixed ADC bit resolutions across the BS antennas can increase the energy efficiency up to 30% compared to equal ADC bit allocation. [ABSTRACT FROM AUTHOR]

This article considers a multi-pair massive multiple-input multiple-output relaying channel where $K$ single-antenna sources communicate with $K$ single-antenna destinations via the assistance of a decode-and-forward relay equipped with massive antenna arrays. The relay station uses maximum-ratio processing to decode the signals transmitted from the sources and precode the signals before broadcasting to the destinations. To perform maximum-ratio processing, the relay needs to know the channels to the sources and the destination. This is done during the training phase where all sources and destinations send pilot sequences to the relay. We consider a very general case in which the pilot sequences are arbitrary. An exact closed-form expression for the end-to-end spectral efficiency is derived taking into account the imperfect channel estimates with arbitrary power control coefficients. From the spectral efficiency formula, we formulate and propose to solve a max-min fairness power allocation. With this power control scheme, the spectral efficiency improves significantly, compared to the uniform power control. In particular, a simple greedy pilot assignment scheme is proposed to reduce the pilot contamination effect, and hence, improve the system performance under the limitations of training duration. [ABSTRACT FROM AUTHOR]

We consider a multi-way decode-and-forward relaying network with very large antenna arrays at the relay station. In this system, each user and the relay operate in half-duplex and time-division duplexing modes. To exchange information among all users, we propose a new transmission protocol which combines massive multiple-input multiple-output technology with linear processing, self-interference cancelation, and successive cancelation decoding. Our proposed transmission protocol reduces the number of time-slots for data exchange among users by approximately 2 times, compared with the conventional data transmission protocol. For this new topology, we derive a very tight approximation of the spectral efficiency in closed-form assuming perfect channel state information (CSI). Then, a CSI acquisition method at the relay and the users is provided and analyzed. We show via numerical simulations, that the performance gap between imperfect and perfect CSI cases is small. The closed-form expression of the spectral efficiency enables us to design two power allocation schemes. In the first power allocation scheme, we choose the transmit powers at the users and the relay to maximize the sum spectral efficiency, subject to a given quality-of-service requirement for each user. In the second power allocation scheme, the objective is the energy efficiency taking into account the hardware power consumption. Both power allocation schemes can be efficiently executed by iteratively solving a sequence of convex problems. Numerical results verify the effectiveness of the proposed transmission protocol and the power allocation schemes compared with the state of the art. [ABSTRACT FROM AUTHOR]

The delay constraints imposed by future wireless applications require a suitable metric for assessing their impact on the overall system performance. Since the classical Shannon's ergodic capacity fails to do so, the so-called effective rate was recently established as a rigorous alternative. While prior relevant works have improved our knowledge on the effective rate characterization of communication systems, an analytical framework encompassing several fading models of interest is not yet available. In this paper, we pursue a detailed effective rate analysis of Nakagami-m, Rician and generalized-K multiple-input single-output (MISO) fading channels by deriving new, analytical expressions for their exact effective rate. Moreover, we consider the asymptotically low and high signal-to-noise regimes, for which tractable, closed-form effective rate expressions are presented. These results enable us to draw useful conclusions about the impact of system parameters on the effective rate of different MISO fading channels. All the theoretical expressions are validated via Monte-Carlo simulations. [ABSTRACT FROM PUBLISHER]

The κ−μ/ inverse gamma and η−μ/ inverse gamma composite fading models are presented and extensively investigated in this paper. We derive closed-form expressions for the fundamental statistics of the κ−μ/ inverse gamma composite fading model, such as the probability density function (PDF), cumulative distribution function (CDF). Additionally, we solve the associated integral that is commonly used to obtain the moment generating function (MGF) of statistical distributions to provide an MGF-type function which is valid for performance analysis over the specified parameter space. Analytic expressions for the PDF, higher order moments and AF are also derived for the η−μ/ inverse gamma composite fading model, while infinite series expressions are obtained for the corresponding CDF and MGF-type function. The suitability of the new models for characterizing composite fading channels is demonstrated through a series of extensive field measurements for wearable, cellular, and vehicular communications. For all of the measurements, two propagation geometry problems with special relevance to the two new composite fading models, namely the line-of-sight (LOS) and non-LOS (NLOS) channel conditions, are considered. It is found that both the κ−μ/ inverse gamma and η−μ/ inverse gamma composite fading models provide an excellent fit to fading conditions encountered in the field. The goodness-of-fit of these two composite fading models is also evaluated and compared using the resistor-average distance. As a result, it is shown that the κ−μ/ inverse gamma composite fading model provides a better fit compared to the η−μ/ inverse gamma composite fading model when strong dominant signal components exist. On the contrary, the η−μ/ inverse gamma composite fading model outperforms the κ−μ/ inverse gamma composite fading model when there is no strong dominant signal component and/or the parameter η is not equal to unity, indicating that the scattered wave power of the in-phase and quadrature components of each cluster of multipath are not identical. [ABSTRACT FROM AUTHOR]

In this paper, we propose a relative channel estimation error (RCEE) metric, and derive closed-form expressions for its expectation \rm Exprcee and the achievable uplink rate holding for any number of base station antennas $M$ , with the least squares (LS) and minimum mean squared error (MMSE) methods. It is found that RCEE and \rm Exprcee converge to the same constant value when $M\rightarrow \infty $ , which renders the pilot power allocation (PPA) substantially simplified and a PPA algorithm is proposed to minimize the average \rm Exprcee per user under a total pilot power budget $P$ in multi-cell massive multiple-input multiple-output systems. Numerical results show that the PPA algorithm brings considerable gains for the LS estimation compared with equal PPA (EPPA), while the gains are significant only with large frequency reuse factor (FRF) for the MMSE estimation. Moreover, for large FRF and large $P$ , the performance of the LS approaches to that of the MMSE. Besides, a scheduling strategy is proposed to allocate pilot power in the whole system, which can approach the optimal performance. For the achievable uplink rate, the PPA scheme and improves the minimum achievable uplink rate compared with the EPPA scheme. [ABSTRACT FROM AUTHOR]