Performance Of MIMO Systems Research Articles

Modified Conjugate Gradient Algorithms for Gram Matrix Inversion of Massive MIMO Downlink Linear Precoding

This paper deals with various low complexity algorithms for higher order matrix inversion involved in massive MIMO system precoder design. The performance of massive MIMO systems is optimized by the process of precoding which is divided into linear and nonlinear. Nonlinear precoding techniques are most complex precoding techniques irrespective of its performance. Hence, linear precoding is generally preferred in which the complexity is mainly contributed by matrix inversion algorithm. To solve this issue, Krylov subspace algorithm such as Conjugate Gradient (CG) was considered to be the best choice of replacement for exact matrix inversions. But CG enforces a condition that the matrix needs to be Symmetric Positive Definite (SPD). If the matrix to be inverted is asymmetric then CG fails to converge. Hence in this paper, a novel approach for the low complexity inversion of asymmetric matrices is proposed by applying two different versions of CG algorithms- Conjugate Gradient Squared (CGS) and Bi-conjugate Gradient (Bi-CG). The convergence behavior and BER performance of these two algorithms are compared with the existing CG algorithm. The results show that these two algorithms outperform CG in terms of convergence speed and relative residue.

Time Shifted Pilot Signal Transmission With Pilot Hopping To Improve The Uplink Performance of Massive MIMO System For Next Generation Network

The paucity of pilot signals in Massive MIMO system is a vital issue. To accommodate substantial number of users, pilot signals are reused. This leads to interference, resulting in pilot contamination and degrades channel estimation at the Base Station (BS). Hence, mitigation of pilot contamination is exigency in Massive MIMO system. The proposed Time Shifted Pilot Signal Transmission with Pilot signal Hopping (TSPTPH), addresses the pilot contamination issue by transmitting pilot signals in non-overlapping time interval with hopping of pilot signals in each transmission slot. Hopping is carried by switching user to new a pilot signal in each transmission slot, resulting in random change of interfering users. This contributes to the change in channel coefficient, which leads to improved channel estimation at the BS and therefore enhances the efficiency of Massive MIMO system. In this system, Uplink Signal Power to Interference plus Noise Power Ratio (SINR) and data-rate are calculated for pilot signal reuse factor 1 and 3, by estimating the channel with Least Square estimation. The proposed system also reduces the uplink Signal power for data transmission of each User Equipment for normalized spectral efficiency with rising number of antennas at the BS and thus improves battery life.

BER Analysis of Hybrid Precoded Massive MIMO Systems in Downlink with Receiver Beamforming over mmwave Channels

Next generation networks are required to deliver extremely high data rates in order to enable mission critical services, massive IoT and enhanced mobile broadband. In the pursuit of high data rates, significant research is focused on higher frequency bands. mmWaves are the most promising carriers because of their associated bandwidth benefits. However, on the other hand, mmWaves also bring along difficulties in link management as the channel is totally different from the traditional systems. This paper evaluates the BER performance of mmWave-massive MIMO systems with Hybrid precoding and receiver beamforming. The availability of perfect CSI at both the transmitting and receiving ends of the downlink is assumed. The results demonstrate that BER performance at low SNR region remains almost exclusive of the system dimensions as long as CSI is available. It was observed that almost 20 dB SNR is required to achieve error performance of 10-5 . Zero forcing and Wiener Filter precoder are also evaluated against each other with analog precoding and receiver beamforming

Effect of Number of Base Station Antennas on the Performance of Massive MIMO System

Effect of Number of Base Station Antennas on the Performance of Massive MIMO System

Scheduling for Multi-User Multi-Input Multi-Output Wireless Networks with Priorities and Deadlines

The spectral efficiency of wireless networks can be significantly improved by exploiting spatial multiplexing techniques known as multi-user MIMO. These techniques enable the allocation of multiple users to the same time-frequency block, thus reducing the interference between users. There is ample evidence that user groupings can have a significant impact on the performance of spatial multiplexing. The situation is even more complex when the data packets have priority and deadlines for delivery. Hence, combining packet queue management and beamforming would considerably enhance the overall system performance. In this paper, we propose a combination of beamforming and scheduling to improve the overall performance of multi-user MIMO systems in realistic conditions where data packets have both priority and deadlines beyond which they become obsolete. This method dubbed Reward Per Second (RPS), combines advanced matrix factorization at the physical layer with recently-developed queue management techniques. We demonstrate the merits of the this technique compared to other state-of-the-art scheduling methods through simulations.

THE PERFORMANCE OF A HYBRID BEAMFORMING mmWAVE MIMO SYSTEM WITH NON-IDEAL HARDWARE

With the increasing wireless data traffic and data rate demands, milimeter-wave band corresponding to the frequency range 30-300 GHz has much attention of the researchers. Using multiple antennas at the transmitter and the receiver with beamforming helps overcome high transmission loss. Therefore, millimeter-wave Multiple-Input Multiple-Output (mmWave MIMO) is a key technology for the next generation wireless communication system. However, due to hardware constrains when operating in the high frequency range, the performance of a mmWave MIMO system will decrease. In this paper, we analysis system performance of a hybrid beamforming mmWave MIMO system with non-ideal hardware (phase noise and quantization noise).

Performance of MIMO and Relay Communication System using TGn and HH Channel

The research on relay communication systems and MIMO has been done by researchers. Both systems have advantages in increasing the system performance and capacity. While the OFDM transmission technique has the advantage to avoid ISI from receiving signals. Systems are simulated to obtain BER as a system performance parameter and determine the increase in BER due to the use of a relay and 2 antennas in communication systems. Systems are compared between relay system with the non-relay system, where both systems are simulated too for using 2 antennas and 1 antenna. Messages are sent using the OFDM technique over TGn and the HH channel. Systems with 2 antennas use the Alamouti scheme. Received messages are combined using MRC, and the original messages are detected using an ML detector at the receiver. The increase in BER obtained between relay systems compared to non-relays is 1.69 and 2.02 times when using 1 and 2 antennas on Eb/No = 9 dB. Increased BER also occurs between 2 antenna systems compared to system 1 antenna, which is 79.71 times in non-relay systems and 94.93 times in relay system on Eb/No = 9 dB. From these results, it can be seen that there is an increase in BER in the use of a relay and 2 antennas in the system. The BER system that occurs, both using the TGn channel and the HH channel, shows relatively the same results.

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.

BER and Capacity Improvement for Multiuser MIMO System by MRT Precoding Technique

In recent years several of endeavors have been conducted in various papers to improve capacity and bit error rate performance of multiuser MIMO system. Every effort tried to increase gain of the individual stream between base station and users’ antennas while reducing the interference among multiple users and interference between streams of single user itself. All these papers adopted precoding techniques for beam forming of individual stream. Various papers have compared precoding techniques such as DPC, BD-ZF, BD-MMSE, BD-QR-MRL, and BD-QR-LRL. Block diagonalization technique is capable to reduce multiuser interference, but not able to combat interference between antennas of single user itself. BD combines with other techniques to overcome this problem. This paper also proposes a precoding technique called modified maximum ratio transmission, which is able to deal with the problem without much complexity. Simulation is done to compare all precoding technique with MRT. The paper tests the precoding techniques on the parameters of BER and capacity, to achieve optimum receiver performance. BER curve and capacity curve are plotted to conclude the paper.

Pulse Position-Based Spatial Modulation for Molecular Communications

Multiple-input-multiple-output (MIMO) approaches have been recently introduced to molecular communications (MC) in order to increase the communication throughput. For MIMO systems, index modulation (IM) suggests encoding information bits using the indices of the available antennas, rather than employing spatial multiplexing or performing other space-time coding schemes. Recent works have shown that utilizing the available MIMO antennas with the IM-based approaches improve the error performance of a molecular MIMO system, courtesy of molecular-IM’s robustness against inter-symbol interference and inter-link interference (ILI). Inspired by IM’s prospects on the MC, this letter proposes a novel family of the IM-based schemes to the MC realm. The proposed schemes combine position-based constellations with antenna indices to encode bits in and yield reliable error performances due to their robustness against the ILI.

Asymptotic Analysis of RZF Over Double Scattering Channels With MMSE Estimation

This paper studies the ergodic sum rate performance of regularized zero-forcing (RZF) precoding in the downlink (DL) of a multiuser multiple-input single-output (MISO) system, where the channel between the base station (BS) and each user is modeled by the double scattering model. This non-Gaussian channel model is a function of both the antenna correlation and the structure of scattering in the propagation environment. This paper first makes the preliminary contribution of deriving the minimum-mean-square-error (MMSE) channel estimate for this model. The system model accounts for channel estimation errors and per-group channel correlation matrices for the users. The analysis assumes that the number of BS antennas, the number of single-antenna users and the number of scatterers in each group grow large while their ratio remains bounded. Under this setting, this paper derives deterministic equivalents of the signal-to-interference plus noise ratio (SINR) and the sum rate which are almost surely tight in the large system limit. The derived approximations are expressed in a closed-form for the special case of multi-keyhole channel. We show that the performance of a massive MIMO system does not scale linearly with the number of antennas under uncorrelated channel conditions and is actually limited by the number of scatterers in the propagation environment. Simulation results confirm the close match provided by the asymptotic analysis for moderate system dimensions.

Deep Clustering-Based Codebook Design for Massive MIMO Systems

Deep learning (DL) can effectively handle explosive data and solve the complicated non-convex problems. Recently, it is used to reduce the overhead of channel state information (CSI) feedback and improve the performance of the limited feedback massive MIMO systems. However, the complex wireless environment and the high-dimensional data of massive MIMO channel degrades the performance of the DL based codebook design. To address this issue, we propose a deep clustering (DC) based codebook design for massive MIMO systems. At first, deep neural network (DNN) learns the key propagation characteristics of the wireless channel according to the training model. And then, the clustering algorithm outputs the centroids of each key propagation characteristic, which can be used to reconstruct the valid space of massive MIMO channel. Finally, massive MIMO codebook is constructed by the valid space. Since the amount of the key propagation characteristics are far less than the dimension of massive MIMO channel, the proposed design can significantly simplify the parameters and the structures of DNN. Moreover, the clustering algorithm output the information with minimum sum-distance with the real channel sequences which can acquire the maximum sum-rate of massive MIMO codebook design. The robustness of the proposed codebook design is validated by carrying out extensive simulation in various scenarios and antenna array structures. Simulation results consist with theoretical analysis in terms of the achievable rate, and demonstrate that the proposed codebook design outperforms the traditional schemes.

Fast Modeling Methods for Estimating Imaging Performance of Whole Body Screening

The simulation of the millimeter wave imaging system for whole body screening before a safety inspection manufactured is a challenging work. The conventional physical optics (PO) method is a proper high-frequency approximation method to solve the forward problem of imaging. In this letter, a modified PO method is used to calculate not only metal scatterer but also nonmetal dielectric medium. A ray tracing method and its modification are proposed to further fast estimate the performance of the multiple-input-multiple-output (MIMO) imaging system. The radiation pattern of transmitter or receiver is taken into account, then the rough imaging performance of arbitrary MIMO system on arbitrary human posture can be acquired in seconds to make the system design flexible and convenient. The image reconstruction of the proposed method for a human body model with dielectric skin medium and metal pistol has demonstrated the applicability to real-life applications.

Sum-Rate Performance of Massive MIMO Systems in Highly Scattering Channel with Semi-Orthogonal and Random User Selection

The sum-rate performance of a massive MIMO system is dependent on the adequate user and antenna selection techniques. It is best when all the selected users are mutually orthogonal (MOU) and antennas are selected based on maximum channel gain. In the case, when number of antennas in massive MIMO is approximately hundreds, the computational complexity cost in joint user and antenna selection is very high. Semi-orthogonal user selection (SUS) is preferred to reduce interference and complexity cost. In highly scattering Rayleigh fading channel random user selection (RUS) technique can be used because of small loss of system sum-rate compared toSUSandMOUtechniques. In this paper we propose a joint user and antenna selection algorithm where users are scheduled using semi-orthogonality measure and antenna selection is based on maximum channel gain. In addition, an algorithm for joint user and antenna selection is reported here with RUS for user selection and maximum channel gain for antenna selection. We explore the system sum-rate performance of a massive MIMO system using these algorithms for the case of a highly scattering Rayleigh fading channel. We consider various precoding techniques MMSE, ZFBF, and MRT and a range of SNR. We also explore the effect of spatial and multiuser diversity on system sum-rates using proposed algorithms. The sum-rate obtained by algorithms-1 is greater than the algorithm-2 about 1–3% but second one is much simpler.

Joint interference alignment and power allocation for NOMA-based multi-user MIMO systems

Interference alignment (IA) and non-orthogonal multiple access (NOMA) are key technologies for achieving the capacity scaling required by next generation networks to overcome the unprecedented growth of data network traffic. Each of these technologies was proved to present excellent performance for MIMO systems. In this article, we propose a joint IA and power allocation (PA) framework for NOMA-based multi-user MIMO (MU-MIMO) systems. Different approaches for applying IA in downlink NOMA-based MU-MIMO systems will be addressed while implementing a PA technique that fully exploits the characteristics of NOMA-based systems. The proposed framework aims to maximize the sum-rate of the NOMA-based MU-MIMO system through combining IA with PA. The process begins by initially grouping the system users into clusters for optimum implementation of NOMA. The sum-rate maximization is carried out under cluster power budget, user quality-of-service (QoS), and robust successive interference cancellation (SIC) constraints. Meanwhile, it uses the power domain multiplexing strategy to allow the users within each cluster to share the data streams without exerting interference to one another. Three iterative joint IA and PA algorithms are proposed for NOMA-based MU-MIMO systems. Moreover, these algorithms are compared with orthogonal multiple access (OMA)-based MU-MIMO counterpart as well as the state-of-the-art techniques presented for NOMA-based MU-MIMO systems. Numerical simulations verify that the proposed framework can greatly improve the performance of NOMA-based MU-MIMO systems in terms of the achievable sum-rate when compared with OMA-based MU-MIMO and the state-of-the-art NOMA-based MU-MIMO systems.

Capacity‐enhancement in MIMO systems using biomimetic electrically small antenna arrays

The authors investigate the performance of multi-input-multi-output (MIMO) communications systems that exploit biomimetic antenna arrays (BMAAs) with electrically small-aperture dimensions. By exploiting the mutual coupling between closely spaced radiating elements and extracting the maximum available power from all excitation modes of the array, BMAAs can significantly outperform conventional antenna arrays with similar aperture sizes. As a proof of concept demonstration, they examine the use of two-element BMAAs consisting of two $\lambda /4$λ/4 monopole antennas with variable element spacing in an MIMO system. The capacity of MIMO systems using such BMAAs is compared with those that use conventional antenna arrays with the same element types and spacing. Their simulation results demonstrate that using BMAAs can offer considerable capacity enhancements in an MIMO system. To experimentally verify these results, a prototype of a two-element BMAA operating at 615 MHz with element spacing of $\lambda /10$λ/10 and a regular array prototype with similar antenna elements and dimensions are fabricated and characterised. The performance of MIMO systems using these two antennas is modelled using numerical channel modelling using the measured antenna responses. These results are found to be in good agreement with theoretical predictions.

Covariance Matrix Estimation in Massive MIMO

Interference during the uplink training phase significantly deteriorates the performance of a massive MIMO system. The impact of the interference can be reduced by exploiting second order statistics of the channel vectors, e.g., to obtain minimum mean squared error estimates of the channel. In practice, the channel covariance matrices have to be estimated. The estimation of the covariance matrices is also impeded by the interference during the training phase. However, the coherence interval of the covariance matrices is larger than that of the channel vectors. This allows us to derive methods for accurate covariance matrix estimation by appropriate assignment of pilot sequences to users in consecutive channel coherence intervals.

Optimal Transmit Antenna Selection for Massive MIMO Wiretap Channels

In this paper, we study the impacts of transmit antenna selection on the secrecy performance of massive MIMO systems. We consider a wiretap setting in which a fixed number of transmit antennas are selected and then confidential messages are transmitted over them to a multi-antenna legitimate receiver while being overheard by a multi-antenna eavesdropper. For this setup, we derive an accurate approximation of the instantaneous secrecy rate. Using this approximation, it is shown that in some wiretap settings under antenna selection the growth in the number of active antennas enhances the secrecy performance of the system up to some optimal number and degrades it when this optimal number is surpassed. This observation demonstrates that antenna selection in some massive MIMO settings not only reduces the RF-complexity, but also enhances the secrecy performance. We then consider various scenarios and derive the optimal number of active antennas analytically using our large-system approximation. Numerical investigations show an accurate match between simulations and the analytic results.

A novel low complexity downlink linear precoding algorithm for massive MIMO systems

The tremendous advancements in 4G and beyond 4G wireless standards requires a high demand for the increased data rate, high spectral efficiency and minimal power requirement. Massive MIMO is a key technology that can be used to attain all the above requirements at the cost of increased complexity. The performance of this massive MIMO system can be optimized by simple linear precoding techniques, the complexity of which lies on the inversion of large size matrix. In this paper, we propose a large scale low complexity matrix inversion algorithm which is highly suitable for parallel architecture. The proposed algorithm makes use of Chebyshev polynomial and Weyl’s inequality and named as Weyl’s Chebyshev acceleration (WCA) algorithm. This algorithm is further simplified by exploiting the diagonal dominance property of the positive definite Hermitian Gram matrix that is to be inverted. The specialty of this algorithm is, it is inner product free which makes this highly suitable for parallel computing environment and thus the algorithm becomes speedy. The performance of the proposed algorithm is evaluated in urban micro cell scenario and is proven to be more efficient in terms of BER performance and complexity. Also the proposed WCA based precoding algorithm achieves approximately 50% of complexity saving in the total flop count in comparison with the existing algorithms for the micro cell scenario. The BER performance reaches the near optimal results of ZF algorithm as SNR increases.

Performance Analysis of Linear Receivers for Uplink Massive MIMO FBMC-OQAM Systems

Offset-quadratic-amplitude-modulation-based filterbank multicarrier (FBMC-OQAM) has been shown to be a promising alternative to cyclic prefix-orthogonal frequency division multiplexing. More recently, the use of FBMC-OQAM has been proposed in combination with massive MIMO communications. In this context, it is interesting to study the overall effect of massive MIMO on the FBMC-OQAM intrinsic interference and its interaction with channel frequency selectivity. In this paper, the performance of an FBMC-OQAM uplink massive MIMO system is theoretically characterized in terms of the output mean squared error (MSE) of the estimated transmitted symbols and for three types of linear receivers, namely, zero forcer, linear minimum mean squared error, and matched filter. Using random matrix theory, the output MSE of these receivers is asymptotically characterized as the number of base station antennas $N$ and the number of users $K$ grow large, while keeping a finite ratio $N/K$ . The obtained expressions allow to draw many conclusions, some of which were already noticed in the literature but not yet theoretically proven. First, the MSE becomes uniform across the frequency band as a result of the channel hardening effect. Second, it is shown that a good synchronization of the users is crucial in a massive MIMO scenario. Finally, if the users are well synchronized, the different terms that compose the MSE, such as noise, interuser interference, and the distortion caused by the channel frequency selectivity, become negligible for large values of the ratio $N/K$ . This effect was previously referred to as “self-equalization” in the literature.