Downlink Massive MIMO Systems Research Articles

Performance analysis of downlink massive MIMO system with precoding techniques and pilot reuse factor

Performance analysis of downlink massive MIMO system with precoding techniques and pilot reuse factor

Dual iterative algorithm for hybrid beamforming in mmWave downlink massive multi-user MIMO systems

Dual iterative algorithm for hybrid beamforming in mmWave downlink massive multi-user MIMO systems

Performance Analysis of Linear Precoding in Downlink Based on Polynomial Expansion on Massive MIMO Systems

The performance of linear precoding schemes in downlink Massive MIMO systems is dealt with in this paper. Linear precoding schemes are incorporated with zero-forcing (ZF) and maximum ratio transmission (MRT), truncated polynomial expansion (TPE), regularized zero force (RZF) in Downlink massive MIMO systems. Massive MIMO downlink output is evaluated with linear precoding included. This paper expresses the performance of achievable sum-rate linear precoding with variable signal-to-noise (SNR) ratio and achievable sum rate and several transmitter-receiver antennas, such as imperfect CSI, less complex processing, and inter-user interference. The transmitter has complete state information on the channel. The information narrates how a signal propagates to the receiver from the transmitter and reflects, for example, the cumulative effect of distance scattering, fading, and power decay. They show that the performance analysis of two linear precoding techniques, i.e., Maximum Ratio Transmission (MRT) and Zero Forcing (ZF) for downlink mMIMO output network over a perfect chain. The results show the improved ZF precoding achievable sum rate compared to the MRT precoding schemes and compared the average achievable rate RZF and TPE.

Joint Resource Allocation for Linear Precoding in Downlink Massive MIMO Systems

We study joint proportional-fair (PF) resource allocation (RA), including user selection, linear precoding design, power optimization, and modulation and coding scheme selection, in a single-cell downlink massive MIMO (m-MIMO) system over consecutive time-slots when taking per-antenna power constraints (PAPCs) into account. We formulate the general PF joint RA optimization problem as a weighted sum-rate maximization problem at each time-slot and develop a solution technique to obtain a quasi-optimal feasible solution via the introduction of auxiliary variables and a carefully chosen approximation of the spectral-efficiency function. To obtain results for larger settings (i.e., larger number of antennas and users), we propose an approximation to the general problem that yields quasi-optimal feasible solutions. Moreover, we consider state-of-the-art linear precoding techniques and propose a general heuristic RA scheme that takes PAPCs into account. Numerical results show that PAPCs have significant impact on performance even for a very large number of antennas, and that the best existing linear precoding technique, RZFT (regularized zero-forcing transmission) performs very well when RA is performed carefully as long as the PAPCs are not tight. However, RZFT is far from optimal under tight PAPCs, which highlights the need for practical PAPC-aware precoding techniques in this regime.

Statistical Beamforming for FDD Downlink Massive MIMO via Spatial Information Extraction and Beam Selection

In this paper, we study the beamforming design problem in frequency-division duplexing (FDD) downlink massive MIMO systems, where instantaneous channel state information (CSI) is assumed to be unavailable at the base station (BS). We propose to extract the information of the angle-of-departures (AoDs) and the corresponding large-scale fading coefficients (a.k.a. spatial information) of the downlink channel from the uplink channel estimation procedure, based on which a novel downlink beamforming design is presented. By separating the subpaths for different users based on the spatial information and the hidden sparsity of the physical channel, we construct near-orthogonal virtual channels in the beamforming design. Furthermore, we derive a sum-rate expression and its approximations for the proposed system. Based on these closed-form rate expressions, we develop two low-complexity beam selection schemes and carry out asymptotic analysis to provide valuable insights on the system design. Numerical results demonstrate a significant performance improvement of our proposed algorithm over the state-of-the-art beamforming approach.

Hybrid combiner design for downlink massive MIMO systems

We consider a hybrid combiner design for downlink massive multiple-input multiple-output systems when there is residual inter-user interference and each user is equipped with a limited number of radio frequency (RF) chains (less than the number of receive antennas). We propose a hybrid combiner that minimizes the mean-squared error (MSE) between the information symbols and the ones estimated with a constant amplitude constraint on the RF combiner. In the proposed scheme, an iterative alternating optimization method is utilized. At each iteration, one of the analog RF and digital baseband combining matrices is updated to minimize the MSE by fixing the other matrix without considering the constant amplitude constraint. Then, the other matrix is updated by changing the roles of the two matrices. Each element in the RF combining matrix is obtained from the phase component of the solution matrix of the optimization problem for the RF combining matrix. Simulation results show that the proposed scheme performs better than conventional matrix-decomposition schemes.

Massive MIMO with Transceiver Hardware Impairments: Performance Analysis and Phase Noise Error Minimization

In this paper, we investigate the impact of hardware impairments (HWIs) on the performance of a downlink massive MIMO system. We consider a single-cell system with maximum ratio transmission (MRT) as precoding scheme, and with all the HWIs characteristics such as phase noise, distortion noise, and amplified thermal noise. Based on the system model, we derive closed-form expressions for a typical user data rate under two scenarios: when a common local oscillator (CLO) is used at the base station and when separated oscillators (SLOs) are used. We also derive closed-form expressions for the downlink transmit power required for some desired per-user data rate under each scenario. Compared to the conventional system with ideal transceiver hardware, our results show that impairments of hardware make a finite upper limit on the user’s downlink channel capacity; and as the number of base station antennas grows large, it is only the hardware impairments at the users that mainly limit the capacity. Our results also show that SLOs configuration provides higher data rate than CLO at the price of higher power consumption. An approach to minimize the effect of the hardware impairments on the system performance is also proposed in the paper. In our approach, we show that by reducing the cell size, the effect of accumulated phase noise during channel estimation time is minimized and hence the user capacity is increased, and the downlink transmit power is decreased.

Antenna selection and transmission power for energy efficiency in downlinkmassive MIMO systems

Massive multiinput-multioutput (M-MIMO) systems are crucial for maximizing energy efficiency (EE) in fifth-generation (5G) wireless networks. A M-MIMO system's achievable high data rate is highly related to the number of antennas, but increasing the number of antennas the system raises energy consumption. In this paper, we derive ergodic EE based on the optimal transmit power and joint optimization antenna selection (AS) with impact pilot reuse sequences (PRSs). We apply Newton's method and the Lagrange multiplier to derive jointly optimized AS and optimal transmission power under the effect of PRSs. The proposed algorithm prevents repeated searching for joint optimal AS and optimal transmission power to reduce the complexity caused by an increasing number of antennas. From the simulation results, we conclude that EE could be maximized by employing the minimal PRSs and transmission power that are greater than the circuit's power consumption. The proposed algorithm offers maximum EE by repeating a minimizing pilot signal until the optimal AS and transmission power are achieved.

An Efficient Precoding Method for Improved Downlink Massive MIMO System

This paper proposes an efficient precoding method based on Neumann series (NS) to improve error performances for already developed diagonal NS (DNS) in massive MIMO system. The conventional DNS has very low complexity compared to a zero-forcing (ZF) and any other NS based ZF precoding methods such as tri-diagonal NS (TNS) and eigenvalue based NS. However, the conventional DNS has very poor error performance in highly correlated massive MIMO system and performance degradations are severe as the used modulation is large. For an efficient precoding, diagonal plus columns NS (DCNS)-1, DCNS- $k$ , and hybrid DCNS-1 and DCNS- $U$ are proposed, and these precoding schemes are adaptively used according to the number of total diagonal dominant active users. The DCNS-1 is applied to fully diagonal dominant users and DCNS- $k$ is applied to non diagonal dominant users, and finally, hybrid DCNS-1 and DCNS- $U$ is applied to partially diagonal dominant systems. For improved DCNS- $k$ , $k$ active users which cause the largest post interference power are selected by simple calculations. The simulation results show that bit error rate (BER) performance for the proposed scheme is very higher than the conventional DNS and is nearly approximated to the BER performance for the conventional optimal ZF with very low complexity.

Equal-Gain Transmission in Massive MIMO Systems Under Ricean Fading

This paper considers a multicell downlink (DL) massive MIMO system operating over Ricean fading channels in which each base station (BS) is equipped with a massive antenna array, while each user has a single antenna. We explore equal-gain transmission (EGT), line-of-sight (LOS) component-based EGT (LOS-EGT) and maximum-ratio transmission (MRT) under imperfect channel state information. Closed-form expressions for lower bounds of the achievable rates are derived for EGT over Ricean and Rayleigh fading channels, and for LOS-EGT and MRT over Ricean fading channels. With the obtained closed-form expressions, various power scaling laws concerning DL data transmit power and uplink (UL) pilot transmit power are established and discussed. In particular, it is found that, as the number of BS antennas $M$ grows unlimited, the lower bounds on the rates achieved with EGT, LOS-EGT and MRT schemes approach infinity and are not affected by pilot contamination, while the DL data transmit power and UL pilot transmit power can be scaled down proportionally to ${M^{ -a}}$ and ${M^{ - b}}$ (where $0 \leq a and $b > 0$ ), respectively. Numerical results corroborate the tightness and accuracy of these closed-form expressions and they also show that, when the number of antennas and intercell interference level are large, compared to the MRT, EGT and LOS-EGT are more resistant to intercell interference and pilot contamination.

Downlink Massive MIMO Systems: Achievable Sum Rates and Energy Efficiency Perspective for Future 5G Systems

To meet up with the ever increasing subscribers' demand for higher data rates and mobile data traffic growth in the telecommunication industry, the fifth generation (5G) systems is being considered for the next future cellular communication standards. The two principal design requirements being aimed at in 5G are robust data transmission rates in Gigabits and low power consumption systems. Massive multiple input multiple output (M-MIMO) technology is an evolving smart antenna technology which has some key promising potentials to boost 5G networks in meeting the aforementioned requirements. However, there is an emergent concern that increased number of antenna arrays in M-MIMO system could induce high power consumption and poor energy efficiency when deployed at the base stations (BSs). Also, inter-cellular interference which occurs as a result of pilot contamination, fast fading and uncorrelated noise effects in the radio channels are other open issues in M-MIMO system. This work investigates and compare the achievable sum rates and energy efficiency of a downlink single cell M-MIMO systems utilizing linear and nonlinear precoding schemes. First, we have shown how the increasing signal-to-noise ratio and M-antennas impact the achievable sum rates. Furthermore, the energy saving potentials of M-MIMO systems in macro, micro and pico cellular environments when linear and nonlinear precoding schemes are utilized at the BS have been demonstrated. Particularly, by means of power fairness index, the tradeoff among the energy efficiency, sum rate and the system users have also been presented and discussed. Results show that substantial energy efficiency improvements can be achieved in micro and pico cellular environments of downlink M-MIMO systems when non-linear successive interference cancellation precoding is applied compared to linear precoding schemes.

Approaches of approximating matrix inversion for zero-forcing pre-coding in downlink massive MIMO systems

Several approximation approaches including the Gauss–Seidel (GS) method have been proposed to reduce the complexity of matrix inversion for zero-forcing pre-coding in massive multiple-input–multiple-output systems. However, extra computation is required to obtain the matrix inversion from the iteration result of the GS method. In this paper, we propose a new GS-based matrix inversion approximation (GSBMIA) approach. Unlike the traditional GS method, the GSBMIA approach approximates the matrix inversion, which will simplify further calculations. Furthermore, in order to speed up convergence, we propose a joint algorithm based on the GSBMIA and Newton iteration method where the GSBMIA approach is employed to provide an efficient searching direction for the following Newton iterations. Compared with other approximation methods, the joint algorithm can accommodate more single antenna users for the same base station antenna number. Simulation results demonstrate that the joint algorithm and the GSBMIA approach converge faster than the Neumann series and Newton iteration method.

Beamforming Only Based on Specular Component for Downlink Massive MIMO Systems

In this paper, we are concerned with a multiuser downlink massive MIMO system operating over Ricean fading channels where each user can be equipped with one or multiple antennas. We present a beamforming (BF) transmission scheme that is only based on the specular component, which can reduce efficiently the heavy overhead for channel estimation. For the individual achievable rates, we particularly analyze their power-scaling law when the transmit power per user is scaled down by the number of antennas at the base station (BS). It is found that the individual rates of the proposed BF can be higher than the corresponding rates of the BF based on the scattered and specular components if the specular component is relatively strong. In addition, it is shown that each user can asymptotically achieve the same rate as in the single-user case when both the numbers of BS antennas and the user terminals go to infinity with a fixed ratio. Thus we conclude that the massive MIMO systems may be more suitable to be deployed in Ricean fading rather than Rayleigh fading.

Analysis and Evaluation of Performance Gains and Tradeoffs for Massive MIMO Systems

Massive MIMO technique offers significant performance gains for the future of wireless communications via improving the spectral efficiency, energy efficiency and the channel quality with simple linear processing such as maximum-ratio transmission (MRT) or zero-forcing (ZF) by providing each user a large degree of freedom. In this paper, the system performance gains are studied in a multi-cell downlink massive MIMO system under the main considerations such as perfect channel estimation, imperfect channel estimation and the effect of interference among cells due to pilot sequences contamination. Then, mathematical expressions are derived for these gains i.e., spatial multiplexing gain, array gain and spatial diversity gain. After that, essential tradeoffs among these gains are considered under the effect of non-orthogonal interference, these tradeoffs are: spatial diversity gain vs. spatial multiplexing gain and array gain vs. spatial multiplexing gain. Simulation results show that the unbounded number of base station antennas boosts the array gain through concentrating the energy to spatial directions where users are sited, hence diminishing loss in array gain due to pilot contamination. The simulation results reveal also that massive MIMO strengthens the spatial multiplexing gain through increasing the number of served users via the same system resources in spite the effect of inter-cell interference. Finally, the spatial diversity gain is measured in term of outage probability and the simulation results show that raising the number of antennas will improve the outage probability. Meanwhile increasing the number of served users will lead to degrade the outage probability per user due to non-orthogonal interference from other cells.

Downlink Hybrid Information and Energy Transfer With Massive MIMO

We consider a downlink massive MIMO system, where the base station simultaneously sends information and energy to information users and energy users, respectively. The aim is to maximize the minimum harvested energy among the energy users while meeting the rate requirements of information users. With perfect channel state information (CSI), the problem is solved by obtaining the asymptotically optimal power allocation of information users and the combination coefficients of the energy precoder. For the CSI estimation in time-division duplex systems, orthogonal pilot sequences are employed by information users during the uplink, and one common pilot sequence is shared by all energy users. It is shown that the energy-harvesting performance of such a shared pilot scheme is always better than that of the orthogonal pilot scheme. Further, exploiting the intercell interference in multicell systems, a joint precoder is proposed for cooperative energy transfer, for which both the centralized and distributed implementations are given. Results indicate that the cooperative energy transfer always outperforms the noncooperative scheme with either perfect or estimated CSI.

The Analysis and Comparison of Energy Efficiency Based on Downlink Massive MIMO System

The Analysis and Comparison of Energy Efficiency Based on Downlink Massive MIMO System

Performance analysis for downlink massive MIMO system with ZF precoding

ABSTRACTThis paper investigates the performance for the downlink massive multiple‐input multiple‐output system when the base station serves multiple user terminals (UTs) using zero‐forcing precoding. The tight lower bound of average area spectrum efficiency ( A2SE) is derived as a function of the number of transmission antennas, the number of UTs and the equivalent transmission signal‐to‐noise ratio. Regarding the lower bound as the approximate A2SE, the optimal number of UTs maximising the A2SE is attained for given the number of transmission antennas and the equivalent transmission signal‐to‐noise ratio. After formulating the realistic power consumption model in consideration of both the transmission power and circuit power, the trade‐off between energy efficiency (EE) and A2SE is established, and the optimal EE with respect to A2SE is deduced. Moreover, both the outage probability and bit error ratio expressions are derived related to the degrees of freedom, defined as the difference between the number of transmission antennas and the number of UTs. Simulation results coincide to the analysis well, and they indicate that deploying more transmission antennas or multiplexing a rational number of UTs can improve the A2SE and EE, increasing the degrees of freedom will better both the outage probability and bit error ratio. Copyright © 2013 John Wiley & Sons, Ltd.