Spatial Channel Degrees of Freedom for Optimum Antenna Arrays

One of the ultimate goals of future wireless networks is to maximize data rates to accommodate bandwidth-hungry services and applications. Thus, extracting the maximum amount of information bits for given spatial constraints when designing wireless systems will be of great importance. In this paper, we present antenna array topologies that maximize the communication channel capacity for given number of array elements while occupying minimum space. Capacity is maximized via the development of an advanced particle swarm optimization (PSO) algorithm devising optimum standardized and arbitrarily-shaped antenna array topologies. Number of array elements and occupied space are informed by novel heuristic spatial degrees of freedom (SDoF) formulations which rigorously generalize existing SDoF formulas. Our generalized SDoF formulations rely on the differential entropy of three-dimensional (3D) angle of arrival (AOA) distributions and can associate the number of array elements and occupied space for any AOA distribution. The proposed analysis departs from novel closed-form spatial correlation functions (SCFs) of arbitrarily-positioned array elements for all classes of 3D multipath propagation channels, namely, isotropic, omnidirectional, and directional. Extensive simulation runs and comparisons with existing trivial solutions verify correctness of our SDoF formulations resulting in optimum antenna array topologies with maximum capacity performance and minimum space occupancy

Multi-Antenna Array Topologies Optimization for Future Wireless Networks by Employing Particle Swarm Optimization

The purpose of this work is to design novel antenna array topologies that maximize channel capacity. Accordingly, we employ the particle swarm optimization (PSO) algorithm as an effective technique in similar electromagnetic problems. We use a novel modelling approach to derive the spatial fading correlation function by employing a generic three-dimensional (3-D) angle of arrival (AOA) model. We then employ the PSO algorithm to find the antenna array topology that maximizes the channel capacity. The use of the PSO algorithm together with the new modelling approach for the spatial correlation is sufficiently tested and verified in terms of efficiency and correctness of addressing similar type of electromagnetic problems. Moreover, the general AOA model of this work is adaptable to different propagation environments, thus our approach is very promising in this regard

Spatial channel degrees of freedom for optimum antenna arrays

One of the ultimate goals of future wireless networks is to maximize data rates to accommodate bandwidth-hungry services and applications. Thus, extracting the maximum amount of information bits for given spatial constraints when designing wireless systems will be of great importance. In this paper, we present antenna array topologies that maximize the communication channel capacity for given number of array elements while occupying minimum space. Capacity is maximized via the development of an advanced particle swarm optimization (PSO) algorithm devising optimum standardized and arbitrarily-shaped antenna array topologies. Number of array elements and occupied space are informed by novel heuristic spatial degrees of freedom (SDoF) formulations which rigorously generalize existing SDoF formulas. Our generalized SDoF formulations rely on the differential entropy of three-dimensional (3D) angle of arrival (AOA) distributions and can associate the number of array elements and occupied space for any AOA distribution. The proposed analysis departs from novel closed-form spatial correlation functions (SCFs) of arbitrarily-positioned array elements for all classes of 3D multipath propagation channels, namely, isotropic, omnidirectional, and directional. Extensive simulation runs and comparisons with existing trivial solutions verify correctness of our SDoF formulations resulting in optimum antenna array topologies with maximum capacity performance and minimum space occupancy

Covariance Matrix Evaluation of a Diversity Slot Antenna for Vehicular Communications

A dual-port slot antenna is proposed for vehicular communications. The antenna works at 5.9 GHz in intelligent transportation system (ITS) band. The diversity performance of the design is evaluated using a novel covariance matrix methodology based on reciprocity theorem. The performance evaluation at the early design stage is explained for the first time by relating the radiation pattern of the designed antenna to the effective length matrix. The antenna offers -21 dB of isolation and a minimum gain of 6.5 dB before mounting on the vehicle roof. The evaluated effective diversity gain is 8.6 db

Diversity Antenna for Vehicular Communications in Microwave and mm-Wave Bands

A dual band diversity antenna is proposed for vehicular communications. The antenna works at both 5.9 GHz and 60 GHz simultaneously which makes it a suitable candidate for next generation intelligent transportation systems (ITS). High isolation of the two antenna elements with transmission less than -25 dB at both bands guarantees an optimum diversity performance. The theoretical limit of the diversity gain according to the propagation condition is investigated. It is shown that the effective diversity antenna gain (DAG) of the design is 8.7 dB in a uniform propagation scenario which is only 0.04 dB less than the theoretical limit

Optimal Antenna Array Topologies for Energy Efficiency Maximization by Employing Particle Swarm Optimization

The purpose of this work is to design novel antenna array topologies that maximize the energy efficiency (EE) in multiple-input-multiple-output (MIMO) wireless systems. To provide insights into EE optimization issues, the particle swarm optimization (PSO) algorithm is employed as an effective technique. First, we adopt a flexible and generalized three-dimensional (3D) angle of arrival (AOA) model to account for realistic propagation environments. Then we derive a novel closed-form spatial correlation function (SCF) relevant to the locations of antenna array elements in the 3D space. In this paper, we incorporate our SCF into the EE derivation and apply the PSO algorithm to find the optimal antenna array topology in space that maximizes the EE. The derived EE is significantly higher compared to existing state-of-the art research that employed an exponential SCF. We provide new insights into EE maximization for antenna arrays, where the simulation results demonstrate the effectiveness and usefulness of the proposed approach