Number Of Antenna Arrays Research Articles

Cell-Free Massive MIMO Systems With Non-Ideal Hardware: Phase Drifts and Distortion Noise

In this paper, a generalized uplink cell-free massive multiple-input multiple-output (mMIMO) system with hardware imperfections is investigated. Specifically, the hardware impairments consist of multiplicative phase drifts, additive distortion, and amplified thermal noise. Leveraging on a generic hardware impairment model, closed-form expressions for the channel estimation and achievable rate are presented. Based on these tractable results, we explore the uplink achievable rate surrounding the key design parameters, i.e., the channel estimation error, the number of antenna arrays, the local oscillator (LO) setup, and the variance of phase drifts. Aside from this, we also design a power optimization algorithm to maximize the sum-rate under variant channel use. The weighted minimum mean square error (MMSE) methodology is introduced to iteratively determine the solution in closed form. Numerical simulations validate the analytical analyses and examine the effectiveness of the proposed power control algorithm.

Designing large-scale antenna array using sub-array

Antenna array of large scale have been examined for different applications including 5G technology. To get better data rate or a reliable link substantial number of antenna arrays have been utilized to provide high multiplexing gains as well as array gains with high directivity. In this paper a simple but efficient implementation technique of using sub-arrays for the improvement of large-sized uniform arrays. By repeating a small sub-array multiple times large arrays can be designed. This implication of utilizing small array simplifies the design of a larger array which allows the designer to concentrate on the smaller sub-array before assembling larger arrays. So, by investigating the sub arrays the performance and radiation characteristics of large arrays can be anticipated. The array-factor for a planar sub-array of 2x2 (4 elements) is analyzed using Mat-lab software and then a large array is formed by placing the 2x2 sub-array indifferent configurations in a rectangular arrangements up to 8x8 planar array. And then the results are validated with CST (Computer simulation technology) simulation results.In this way the array-factors, directivities, HPBWs, and side lobes of the constructed large arrays are analyzed and associated with the small sub-array.

Radio propagation and wireless coverage of LSAA-based 5G millimeter-wave mobile communication systems

Millimeter-wave (mmWave) communications will be used in fifth-generation (5G) mobile communication systems, but they experience severe path loss and have high sensitivity to physical objects, leading to smaller cell radii and complicated network architectures. A coverage extension scheme using large-scale antenna arrays (LSAAs) has been suggested and theoretically proven to be cost-efficient in combination with ultradense small cell networks. To analyze and optimize the LSAA-based network deployments, a comprehensive survey of recent advances in statistical mmWave channel modeling is first presented in terms of channel parameter estimation, large-scale path loss models, and small-scale cluster models. Next, the measurement and modeling results at two 5G candidate mmWave bands (e.g., 28 GHz and 39 GHz) are reviewed and compared in several outdoor scenarios of interest, where the propagation characteristics make crucial contributions to wireless network designs. Finally, the coverage behaviors of systems employing a large number of antenna arrays are discussed, as well as some implications on future mmWave cellular network designs.

Energy-Efficient Resource Allocation in Uplink Multiuser Massive MIMO Systems

Energy-efficient communications, namely, green communications, has attracted increasing attention due to energy shortage and greenhouse effect. Motivated by this, we consider the uplink energy-efficient resource allocation in multiuser massive multiple-input multiple-output (MIMO) systems. Specifically, we consider that both the number of antenna arrays at the base station (BS) and the transmit data rate at UE are adjusted adaptively to maximize the energy efficiency. Firstly, we demonstrate the existence of a unique resource allocation solution that is globally optimal by exploiting the properties of objective function. Then we develop an iterative algorithm to solve it. By transforming the originally fractional optimization problem into an equivalent subtractive form using the properties of fractional programming, we develop another efficient iterative resource allocation algorithm. Simulation results have validated the effectiveness of the proposed two algorithms and have shown that both algorithms can fast converge to a near-optimal solution in a small number of iterations.

Energy-efficiency resource allocation of very large multi-user MIMO systems

With increasing demand in multimedia applications and high data rate services, energy consumption of wireless devices has become a problem. At the user equipment side, high-level energy consumption brings much inconvenience, especially for mobile terminals that cannot connect an external charger, due to an exponentially increasing gap between the available and required battery capacity. Motivated by this, in this paper we consider uplink energy-efficient resource allocation in very large multi-user MIMO systems. Specifically, both the number of antenna arrays at BS and the transmit data rate at the user are adjusted to maximize the energy efficiency, in which the power consumption accounts for both transmit power and circuit power. We proposed two algorithms. Algorithm1, we demonstrate the existence of a unique globally optimal data rate and the number of antenna arrays by exploiting the properties of objective function, then we develop an iterative algorithm to obtain this optimal solution. Algorithm2, we transform the considered nonconvex optimization problem into a convex optimization problem by exploiting the properties of fractional programming, then we develop an efficient iterative resource allocation algorithm to obtain this optimal solution. Our simulation results did not only show that the the proposed two algorithms converge to the solution within a small number of iterations, but demonstrated also the performances of the proposed two algorithms are close to the optimum. Meanwhile, it also shows that with a given number iterations the performance of proposed algorithm1 is superior to proposed algorithm2 under small p C . On the contrary, the performance of proposed algorithm2 is superior to proposed algorithm1 under large p C .

Performance of Layered Steered Space–Time Codes in Wireless Systems

Layered Steered Space–Time Codes (LSSTC) is a recently proposed multiple-input multiple-output (MIMO) system that combines the benefits of vertical Bell Labs space–time (VBLAST) scheme, space–time block codes (STBC) and beamforming. In this paper, we derive the error performance and capacity of a single-user LSSTC system. The analysis is general enough to any layer ordering and modulation schemes used. In addition, the derived analysis is general for any LSSTC structure in which layers may have different number of antenna arrays and may be assigned power according to any power allocation. Furthermore, we analytically investigate the tradeoff between the main parameters of the LSSTC system, i.e., diversity, multiplexing and beamforming. Our results give recursive expressions for the probability of error for LSSTC which showed nearly perfect match to the simulation results. Results have also revealed the possibility of designing an adaptive system in which it was shown that combining beamforming, STBC, and VBLAST has better performance than VBLAST at high SNR range.

Fault Tolerant Wireless Mesh Network: An Approach

Wireless mesh networks (WM Ns) have achieved significant development because of fast deployment, easy maintenance and low investment compared with traditional wireless networks. Since WM Ns are typically used as wireless backbones, they have the nature that the wireless communication is not constant. Hence, it is important to defend them against link or node failures. In this paper we present an innovative algorithm for fault-tolerant base station planning using antenna arrays in the backbone networks. The algorithm first detects the node’s as well as link failure’s and then rectifies them using our proposed algorithm. Our paper propose a solution for building a fault tolerant network that can tolerate up to n faults where n is the number of antenna arrays used.