Single-user System Research Articles

Effective hydropower renewable energy source selection using fuzzy neutrosophic boundary approximate area

Small hydropower plants in rural areas are contributing to marginal economic growth and social progress, but their social sustainability assessment is under-studied. Previous studies have shown that no single renewable energy source (RES) can fully meet all sustainability criteria, despite their focus on single-user systems. Scaled renewable energy systems have varying impacts across different systems, involving technical, environmental, social, and economic aspects. This paper proposes a Triangular Fuzzy Neutrosophic Numbers (TFNNs) as an extension of the multi-attributive border approximation area comparison (MABAC) method for hybrid multi-criteria decision-making (MCDM). The proposed method is utilized to assess the selection of hydropower as the most efficient and sustainable renewable energy source for society. Pairwise comparison matrices were used to determine priority vectors and weighted averages of indicators for seven criteria. The evaluation framework analyzed five key dimensions of hydropower plants. The most stable renewable energy source, pumped storage hydropower (60.78%), was found to be followed by run-of-river hydropower (56.39%), impoundment hydropower (50.03%), storage hydropower (39.78%), and offshore hydropower (07.95%). The study offers valuable insights for policymakers and implementer on sustainable electricity solutions for hydropower. Pumped storage hydropower (PSH) improves facility efficiency by ensuring optimal operation of coal and nuclear generators without energy loss. The system can provide a stable and reliable power storage solution for renewable energy sources like wind and solar.

Beyond Diagonal Reconfigurable Intelligent Surfaces: A Multi-Sector Mode Enabling Highly Directional Full-Space Wireless Coverage

Reconfigurable intelligent surface (RIS) has gained much traction due to its potential to manipulate the propagation environment via nearly-passive reconfigurable elements. In our previous work, we have analyzed and proposed a beyond diagonal RIS (BD-RIS) model, which is not limited to traditional diagonal phase shift matrices, to unify different RIS modes/architectures. In this paper, we create a new branch of BD-RIS supporting a multi-sector mode. A multi-sector BD-RIS is modeled as multiple antennas connected to a multi-port group-connected reconfigurable impedance network. More specifically, antennas are divided into <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> ≥ 2) sectors and arranged as a polygon prism with each sector covering 1/ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> space. Different from the recently introduced concept of intelligent omni-surface (or simultaneously transmitting and reflecting RIS), the multi-sector BD-RIS not only achieves a full-space coverage, but also has significant performance gains thanks to the highly directional beam of each sector. We derive the constraint of the multi-sector BD-RIS and the corresponding channel model taking into account the relationship between antenna beamwidth and gain. With the proposed model, we first derive the scaling law of the received signal power for a multi-sector BD-RIS-assisted single-user system. We then propose efficient beamforming design algorithms to maximize the sum-rate of the multi-sector BD-RIS-assisted multiuser system. Simulation results verify the effectiveness of the proposed design and demonstrate the performance enhancement of the proposed multi-sector BD-RIS.

Hankel determinant and orthogonal polynomials for a perturbed Gaussian weight: From finite n to large n asymptotics

We study the monic polynomials Pn(x; t), orthogonal with respect to a symmetric perturbed Gaussian weight function w(x)=w(x;t)≔e−x21+tx2λ,x∈R, with t&amp;gt;0,λ∈R. This problem is related to single-user multiple-input multiple-output systems in information theory. It is shown that the recurrence coefficient βn(t) is related to a particular Painlevé V transcendent, and the sub-leading coefficient p(n, t) of Pn(x; t) (Pn(x; t) = xn + p(n, t)xn−2 + ⋯) satisfies the Jimbo–Miwa–Okamoto σ-form of the Painlevé V equation. Furthermore, we derive the second-order difference equations satisfied by βn(t) and p(n, t), respectively. This enables us to obtain the large n full asymptotic expansions for βn(t) and p(n, t) with the aid of Dyson’s Coulomb fluid approach in the one-cut case [i.e., λt ≤ 1 (t &amp;gt; 0)]. We also consider the Hankel determinant Dn(t), generated by the perturbed Gaussian weight. It is found that Φn(t), a quantity allied to the logarithmic derivative of Dn(t) via Φn(t)=2t2ddtlnDn(t)−2nλt, can be expressed in terms of βn(t) and p(n, t). Based on this result, we obtain the large n asymptotic expansion of Φn(t) and then that of the Hankel determinant Dn(t) in the one-cut case.

Sustainability assessment of renewable power generation systems for scale enactment in off-grid communities

Sustainable Energy for All (SE4ALL), a United Nations initiative, recognizes the significance of renewable energy systems (RES) in meeting the energy needs of off-grid communities. In Pakistan, the rural population faces challenges in accessing reliable electricity, necessitating the exploration of alternative electrification methods. While previous studies have focused on single-user systems, no single RES fully meets all sustainability criteria. Moreover, the impacts of scaled RES differ significantly from those of single systems, encompassing technological, environmental, social, and economic aspects. This study assessed the sustainability of scaled RES for electrifying off-grid communities using Multi-Criteria Decision Analysis (MCDA) based on the Analytical Hierarchy Process (AHP). The assessment framework considered social, technical, environmental, and economic factors as key dimensions of sustainability. Pairwise comparison matrices were employed to determine priority vectors and weighted averages of indicators for fourteen sub-criteria. The results revealed that solar PV (29.82%) emerged as the most sustainable RES for scaled electrification in selected off-grid regions, followed by solar-thermal (26.79%), wind (23.86%), and biomass energy (19.53%). Each alternative has strengths in different categories, with solar-PV excelling in the environmental (42.30%), biomass in the social (36.18%), solar-thermal in the technical (41.53%), and wind energy in the economic category (39.40%). These findings provide valuable insights for implementers and policymakers seeking sustainable electrification solutions for off-grid communities. They emphasize the importance of aligning RES with the unique needs and goals and advocates for the widespread adoption of solar PV systems as a reliable source of electrification foroff-gridareas.

Flexible broadcast UWOC system using an LCVR-based tunable optical splitter.

For underwater wireless optical communication (UWOC) systems, using an omnidirectional light source to construct a broadcast system will require considerable energy due to high geometric loss and water attenuation. In addition, high-sensitivity photon detectors usually have a limited dynamic range, therefore limiting communication distance. In this Letter, a broadcast UWOC system, based on liquid crystal variable retarders (LCVRs) and polarization beam splitters (PBSs), is proposed to allocate user power in accordance with user-specific channel conditions. By adjusting the driving alternating current (AC) voltage of LCVRs to change the input light polarization, different proportions of light can be allocated to different PBS ports before broadcasting to different users. In a dual-user transmitter for the proof-of-concept, the output power dynamic range and the additional insertion loss for the first user are 19.17 dB and 0.91 dB, respectively. For the second user, the performance degrades to 17.33 dB and 1.26 dB, respectively. The step size of power adjustment is less than 0.063 dB. To verify the effectiveness of power adjustment in UWOC systems, a 7-m/243.2-Mbps single-user UWOC system is designed with a water attenuation coefficient ranging from 0.50 dB/m to 2.35 dB/m. All bit error rates (BERs) can decrease to below the forward error correction (FEC) limit by adjusting the LCVR driving voltage. The adjustable range of communication distance could be extended from 4.2 m to 13.19 m with a channel attenuation coefficient of 1.44 dB/m. Finally, a dual-user UWOC experiment is conducted and proves that the proposed system can still work in a multi-user system. The proposed system is proven to be effective for improving the anti-jamming capability and flexibility of UWOC networks.

Peak to average power ratio reduction techniques based on chirp selection for single and multi‐user orthogonal chirp division multiplexing system

AbstractThis article deals with peak to average power (PAPR) reduction in a single and multi‐user orthogonal chirp division multiplexing (OCDM) context. Two methods for PAPR reduction based on the selection of the frequency variation (up or down) of the chirps are first presented in a single user system. The first technique consists in considering two OCDM signals generated with up and down chirps, respectively, and selecting the one offering lowest PAPR. The second PAPR reduction method is based on usual clipping, and in that case the chirp selection aims to reduce the clipping noise. An adapted receiver is presented, based on the maximum likelihood estimation of the frequency variation (up or down) of the chirp. Then, a general procedure for multi‐user OCDM transmission is introduced, where a sub‐band of the available bandwidth is dedicated to each user, whose frequency of the chirps varies within this sub‐band. Next, the PAPR reduction techniques are generalised to this multi‐user OCDM system. Moreover, a performance analysis of the first PAPR reduction method is developed, and it is shown through simulations that theoretical and numerical results match for both Nyquist rate and oversampled signals. It is also shown that the chirp selection reduces the clipping noise, and improves the bit error rate performance compared with clipping only.

MULTI-OWNER DATA SHARING

In the case of Provable Multiple files Data that changes over time in cloud computing,possession refers to the dynamic transfer of stored data to a cloud server. Multiple files indicate that the data will be replicated on multiple servers. The project owner uploads the data to the cloud server using automatic data capture, and the files are then stored on multiple servers. Data loss due to hacking and server crashes can be avoided by uploading data to multiple servers. By distributing the secret key among the several users, multi-user searchable encryption directly adapts a single-user system to a multi-user environment. This is obviously not capable of achieving user accountability, and in the event of user revocation, it necessitates key renewal among non-revoked users, which then necessitates re-encrypting the external database. These issues might be resolved if the cloud implemented access control before responding to user search requests, but as noted in, access control deployment is prohibitively expensive in practise. To make matters worse, users must maintain a separate set of secrets for authentication and authorization. We introduced a new technique, fully homomorphic encryption (FHE), in this project for multiple data file acquisition, file security, and data corruption. For data protection, we must use the FHE algorithm in this project. There are three of them: keygen, copygen, and taggen.The process described above was carried out in the existing system. Keywords- Multiple file data; Cloud server; Fully homomorphic encryption ; FHE algorithm;

Low-Complexity Adaptive Selection Beamforming for IRS-Assisted Single-User Wireless Networks

To maximize the signal strength in an intelligent reflecting surface (IRS)-assisted wireless network, semidefinite relaxation (SDR) and alternating optimization (AO) methods are widely used in the literature. The AO is more appealing owing to its low computational cost than SDR. This correspondence proposes an adaptive selection beamforming scheme for the IRS-assisted single-user communication systems, which requires a substantially lower computational complexity compared to the AO algorithm. Specifically, we ignore the channel gains of the IRS-user link, determine two low-cost sub-optimal active-beamforming vectors at the transmitter, and calculate the corresponding two passive-beamforming solutions at the IRS. Then, we calculate their total channel gains and the solution that yields a higher gain is selected as the final solution. The proposed scheme offers approximately a 60% reduction in computational complexity compared to the AO at the cost of slight performance degradation only for limited system configurations.

SVM-Based Optimization on the Number of Data Streams for Massive MIMO Systems

For millimeter-wave (mmWave) massive multiple-input and multiple-output (MIMO) systems, hardware cost and power consumption can be reduced via hybrid precoding, while keeping almost the same spectral efficiency (SE) as the fully digital precoding scheme. However, for different hardware configuration and channel environments, system SE varies with the number of transmitted data streams at the transmitter, and hence this should be determined primarily before hybrid precoding design. In this article, for single-user massive MIMO systems, a regression model based on the support vector machine technique is proposed, through which the optimal number of data streams can be obtained automatically based on the propagation characteristics of wireless channels, the number of antennas, and RF chains. To validate the correctness of the proposed model, simulation results are presented under various parameter settings.

Joint Sensing and Communication-Rate Control for Energy Efficient Mobile Crowd Sensing

Driven by the rapid growth of Internet of Things applications, tremendous data need to be collected by sensors and uploaded to the servers for further process. As a promising solution, mobile crowd sensing (MCS) enables controllable sensing and transmission processes of multiple types of data in a single device. Despite the appealing advantages, existing works on MCS have mostly simplified two design issues, namely joint control of sensing and transmission processes and corresponding energy consumption. To address the above issues, a single-user MCS system is considered with a typical MCS device sensing and transmitting data to a server in a given time duration. In particular, there exists a busy time interval when the device is incapable of sensing. To minimize the sensing-and-transmission energy consumption of the device, an optimization problem is formulated, where the sensing and transmission rates are jointly optimized over time subjecting to the constraints on the sensing data sizes, transmission data sizes, data casualty, and busy time of sensing. This problem is highly challenging due to the coupling between the rates as well as the existence of the busy time. To deal with this problem, we first show that it can be equivalently decomposed into two subproblems, corresponding to a search for the amount of data size that needs to be sensed before the busy time (referred to as the height), as well as the control of sensing and transmission rates given the height. Next, we show that the latter problem can be efficiently solved by using the classical string-pulling method, while an efficient algorithm is proposed to progressively find the optimal height without the exhaustive search. Moreover, the solution approach is extended to a more complex scenario where there is a finite-size buffer at the server for receiving data. Last, simulations are conducted to evaluate the performance of the proposed designs.

Analyses of Virtual MIMO Multi-User System Performance with Linear Precoding Schemes Using Indoor Measurements at 5 GHz

In this paper, based on 5 GHz indoor multi-user measurements, linear precoding schemes such as zero-forcing (ZF), minimum mean square error (MMSE) and successive interference cancelation (SIC) are applied in the base station in order to investigate the performance of virtual multi-input multi-output (MIMO) over single-user MIMO system. However, to form a virtual MIMO multi-user system, the resources of two users are brought together. In order to achieve a low spatial correlation, two spaced antennas in the MS have been chosen and four spaced antennas elements in BS have been selected. Therefore, the resources of two users (U1 and U2) are brought together to form a 4 × 4 virtual MIMO multi-user system with the BS. The properties of the user_1 (U1) and user_2 (U2) will be analyzed and compared to those properties of virtual MIMO multi-user system formed by U1 and U2. In most cases, the maximum achievable rate is seen with virtual MIMO multi-user compared to single-user MIMO. So virtual MIMO multi-user is desirable for boosting system capacity than single-user MIMO.

Spectral Efficiency of Precoded 5G-NR in Single and Multi-User Scenarios under Imperfect Channel Knowledge: A Comprehensive Guide for Implementation

Digital precoding techniques have been widely applied in multiple-input multiple-output (MIMO) systems to enhance spectral efficiency (SE) which is crucial in 5G New Radio (NR). Therefore, the 3rd Generation Partnership Project (3GPP) has developed codebook-based MIMO precoding strategies to achieve a good trade-off between performance, complexity, and signal overhead. This paper aims to evaluate the performance bounds in SE achieved by the 5G-NR precoding matrices in single-user (SU) and multi-user (MU) MIMO systems, namely Type I and Type II, respectively. The implementation of these codebooks is covered providing a comprehensive guide with a detailed analysis. The performance of the 5G-NR precoder is compared with theoretical precoding techniques such as singular value decomposition (SVD) and block-diagonalization to quantify the margin of improvement of the standardized methods. Several configurations of antenna arrays, number of antenna ports, and parallel data streams are considered for simulations. Moreover, the effect of channel estimation errors on the system performance is analyzed in both SU and MU-MIMO cases. For a realistic framework, the SE values are obtained for a practical deployment based on a clustered delay line (CDL) channel model. These results provide valuable insights for system designers about the implementation and performance of the 5G-NR precoding matrices.

Graph theory methods for fog computing: A pseudo-random task graph model for evaluating mobile cloud, fog and edge computing systems

The development and efficient application of Fog Computing technologies necessitate complex tasks associated with the management and processing of large data sets, including the creation of low-level networks that guarantee the functioning of end devices within the Internet of Things (IoT) concept. This article presents the utilization of graph theory techniques to address these issues. The proposed graph model enables the determination of fundamental characteristics of systems, networks, and network devices in Fog Computing, including optimal features and methods to maintain them in a functioning condition. This work demonstrates how to create and personalize graph displays by adding labels or highlighting to the graph nodes and edges of pseudo-random task graphs. The task graphs, described and visualized in Matlab code, represent the computational work to perform and data transfer between tasks, expressed in Megacycles per second and kilobits/kilobytes of data, respectively. The task graphs can be applied in both single-user systems, where one mobile device accesses a remote server, and multi-user systems, where many users access a remote server through a wireless channel. This set can be utilized by researchers to evaluate cloud/fog/edge computing systems and computational offloading algorithms.

Secrecy Throughput Maximization for IRS-Aided MIMO Wireless Powered Communication Networks

In this paper, we consider deploying an intelligent reflecting surface (IRS) to enhance the downlink (DL) energy transfer and uplink (UL) information transmission efficiency for secure multiple-input multiple-output (MIMO) wireless powered communication networks (WPCNs). We aim to maximize the secrecy throughput of all users by jointly optimizing the DL/UL time allocation, the energy transmit covariance matrix of hybrid access point (AP), the information transmit beamforming matrix of users and the phase shifts of IRS in DL/UL, subject to constraints of energy/information transmit power at the hybrid AP/users and that of unit-modulus IRS phase shifts for DL/UL. To tackle the non-convex problem, we first transform the original problem into an equivalent form based on the mean-square error (MSE) method given time allocation, and then apply the alternating algorithm to update the optimization variables iteratively. Specifically, the energy covariance matrix and the information beamforming matrix are obtained based on the dual subgradient method. For the IRS phase shifts, we investigate two IRS beamforming reflection setups, namely different DL/UL IRS beamforming and identical DL/UL IRS beamforming. For the former case, the second-order cone programming technique and the Majorization-Minimization algorithm/element by element iterative algorithm are applied to obtain the DL and UL IRS phase shifts, respectively. For the latter case, the IRS phase shifts are obtained by the successive convex approximation technique. To further reduce the computational complexity of the single-user system, we derive the closed-form solutions of IRS phase shifts in each iteration for the two different reflection setups. Simulation results show that all the proposed algorithms can greatly improve the secrecy throughput compared to the conventional system without IRS.

A Joint Hybrid Precoding/Combining Scheme Based on Equivalent Channel for Massive MIMO Systems

Due to its inherent ability in reducing hardware cost and power consumption while maintaining high system capacity, hybrid precoding is deemed as one of the key technologies in the upcoming 5G/6G millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. However, it is challenging to design high performance hybrid precoders/combiners with low computational complexity. In this paper, based on the singular value decomposition (SVD) technique and the concept of equivalent channel, joint hybrid precoding strategies with high spectral-efficiency and low complexity are proposed for both single-user and multi-user massive MIMO systems. Specifically, for single-user massive MIMO scenarios, after transforming the design of hybrid beamforming into the problem of maximizing the square of sum eigenvalues for an equivalent channel, a two-stage successive method is conceived to design the analog precoder and combiner jointly, and the corresponding equivalent channel is constructed. Then, the digital precoding and combining operations are realized directly by applying the SVD technique to the matrix of equivalent channel. Meanwhile, the hybrid precoding strategy is extended to the multi-user scenario for achieving high performance resultant from multi-user diversity. Extensive simulations are conducted to verify the effectiveness of the precoding/combing schemes. The results show that our proposed schemes can achieve superior performance with lower complexity compared to the existing ones.

Who’s Controlling My Device? Multi-User Multi-Device-Aware Access Control System for Shared Smart Home Environment

Multiple users have access to multiple devices in a smart home system – typically through a dedicated app installed on a mobile device. Traditional access control mechanisms consider one unique, trusted user that controls access to the devices. However, multi-user multi-device smart home settings pose fundamentally different challenges to traditional single-user systems. For instance, in a multi-user environment, users have conflicting, complex, and dynamically-changing demands on multiple devices that cannot be handled by traditional access control techniques. Moreover, smart devices from different platforms/vendors can share the same home environment, making existing access control obsolete for smart home systems. To address these challenges, in this paper, we introduce Kratos+ , a novel multi-user and multi-device-aware access control mechanism that allows smart home users to flexibly specify their access control demands. Kratos+ has four main components: user interaction module, backend server, policy manager, and policy execution module. Users can easily specify their desired access control settings using the interaction module that are translated into access control policies in the back-end server. The policy manager analyzes these policies, initiates automated negotiation between users to resolve conflicting demands, and generates final policies to enforce in smart home systems. We implemented Kratos+ as a platform-independent solution and evaluated its performance on real smart home deployments featuring multi-user scenarios with a rich set of configurations (337 different policies including 231 demand conflicts and 69 restriction policies). These configurations also included five different threats associated with access control mechanisms. Our extensive evaluations show that Kratos+ is very effective in resolving conflicting access control demands with minimal overhead. We also performed an extensive user study with 72 smart home users to better understand the user’s needs before designing the system and a usability study to evaluate the efficacy of Kratos+ in a real-life smart home environment.

Joint Transmit-and-Receive Antenna Selection System for MIMO-NOMA With Energy Harvesting

In this paper, outage probability (OP) of a joint transmit and receive antenna selection (JTRAS) scheme is analyzed in multiple-input multiple-output non orthogonal multiple access based downlink energy harvesting (EH) relaying networks. In this dual-hop and amplify-and-forward relaying based network, since the first and second hops are types of single-user and multi-user systems, respectively, the optimal JTRAS and suboptimal majority-based JTRAS schemes are employed in the first and second hops. The theoretical OP analysis is carried out over Nakagami-m fading channels in the cases of perfect and imperfect successive interference cancellation. Finally, Monte Carlo simulations are performed to substantiate the accuracy of the theoretical analysis. It is shown that the optimal power splitting ratios at the EH relay are different for users and the users with good channel conditions have minimum optimal ratios.

Waveform and Beamforming Design for Intelligent Reflecting Surface Aided Wireless Power Transfer: Single-User and Multi-User Solutions

In this paper, we study the waveform and passive beamforming design for intelligent reflecting surface (IRS)-aided wireless power transfer (WPT). Generalized multi-user and low complexity single-user algorithms are demonstrated based on alternating optimization (AO) framework to maximize the weighted sum output direct current (DC), subject to the transmit power constraints and passive beamforming modulus constraints. The input signal waveform and IRS passive beamforming phase shifts are jointly designed as a function of users’ individual frequency-selective channel state information (CSI). The energy harvester nonlinearity is explored and two IRS deployment schemes, namely frequency selective IRS (FS-IRS) and frequency flat IRS (FF-IRS), are modeled and analyzed. This paper highlights the fact that IRS can provide an extra passive beamforming gain on output DC power over conventional WPT designs and significantly influence the waveform design by leveraging the benefit of passive beamforming, frequency diversity and energy harvester nonlinearity. Even though FF-IRS exhibits lower output DC than the ideal FS-IRS, it still achieves substantially increased DC power over conventional WPT designs. Performance evaluations confirm the significant benefits of a joint waveform and passive beamforming design accounting for the energy harvester nonlinearity to boost the performance of single-user and multi-user WPT systems.

An Irregular Tiled Array Technique for Massive MIMO Systems

An irregular tiled array technique is proposed for the application of massive MIMO systems, where the uniformly spaced antenna array elements are irregularly divided into subarrays fed by only one radio frequency (RF) chain separately. As compared to conventional beamforming architecture, the number of RF chains is reduced to one-half or one-quarter of the original number by using domino-shaped subarrays or tetromino-shaped subarrays, respectively. Two beamforming architectures for such a framework are proposed and a minimum mean square error (MMSE) method is applied to design the layouts of irregular arrays efficiently. In the framework of single-user massive MIMO systems, numerical simulation results show that the proposed architectures outperform conventional beamforming architectures and antenna selection architecture under the same number of RF chains conditions. With saving half of the transceivers, the loss of gain of the state-of-the-art sparsely sampled array is 1.9dB in the broadside and 2.2 dB for scanning to 30° in comparison with reference array (i.e., one transceiver per element). By contrast, there is no loss of gain of domino-shaped irregular array (i.e., one transceiver per two elements) in the broadside as compared to reference array and the loss of gain will be about 1.5dB for scanning to 30°.

Joint Transceiver Optimization for IRS-Aided MIMO Communications

Intelligent reflecting surface (IRS) is an emerging cost-efficient technology to enhance communication performance by implementing a large number of passive reflecting elements with tunable phases in wireless systems. In this paper, we propose a general framework for the IRS-aided MIMO system designs under both single-user and multi-user setups, in which the diverse performance metrics including weighted mutual information and weighted MSE, and the realistic multiple weighted power constraint are taken into consideration. Leveraging the alternating optimization approach, the optimal IRS phase shifts are obtained in semi-closed forms. Specifically, based on the matrix-monotonic optimization theory, it is found that optimizing IRS phase shifts is essentially equivalent to tuning the eigenvalues and the corresponding eigenvectors of the MSE matrix. Then the proposed general framework is extended to a multi-user system by introducing a majorization-minimization (MM)-based method for IRS phase shift optimization. Simulation results show that our proposed optimal design brings significant enhancement on the chosen performance metric compared to the traditional MIMO systems without the IRS, and also significantly outperforms various benchmark designs in both single-user and multi-user systems.