Enhanced channel simulator for efficient antenna evaluation

• US 7,941,302 B2
• Filed: 05/30/2008
• Issued: 05/10/2011
• Est. Priority Date: 05/30/2008
• Status: Active Grant

• Current Assignee: Hong Kong Applied Science And Technology Research Institute Co., Ltd.
• Original Assignee: Hong Kong Applied Science And Technology Research Institute Co., Ltd.
• Inventors: I, Chih-Lin, Zhao, Xueyuan, Lee, Chun Kit, Lau, Kin Nang, Pan, Zhengang, Cheng, Roger Shu Kwan
• Primary Examiner(s): PHAN, THAI Q
• Application Number:
  US12/129,896
• Publication Number:
  US 20090299717A1
• Time in Patent Office: 1,075 Days
• Field of Search: 703/2, 703/5, 703/17, 455/226.1, 345/450, 342/457, 375/299
• US Class Current: 703/2
• CPC Class Codes: H04B 17/0087 using auxiliary channels or channel simulators

Abstract

Method and apparatus for channel simulation is disclosed. The claimed invention provides method and apparatus 1200 to simulate a propagation channel, particularly a multiple-input-multiple-input (MIMO) channel. The claimed invention further provides a method and apparatus for efficient optimization of antenna by the enhanced channel simulation. The claimed invention takes both antenna characteristics and channel characteristics as inputs, and output time-varying channel realizations to generate the system metrics as the optimization target for antenna under optimization. The claimed invention advantageous provides enhanced channel simulation to meet the accuracy requirement of antenna evaluation.

Claims

1. A method of simulating a propagation channel, comprising:

obtaining a channel power angular distribution such that one or more receiving clusters are identified at a receiving side of the propagation channel and one or more transmitting clusters are identified at a transmitting side of the propagation channel to map the power relationship between the receiving clusters and the transmitting clusters;

generating a time-varying channel realization sequence which represents how the response of the propagation channel varies with time by using the relationship between the receiving clusters and the transmitting clusters and one or more actual antenna radiation patterns as measured from one or more antennae;

adding an antenna element isolation effect to said time-varying channel realization sequence such that the response of the propagation channel includes mutual coupling impedance; and

applying baseband abstraction to the time varying channel realization sequence to generate one or more effects of the propagation channel including, but not limited to, one or more of, scattering, diffraction, and line-of-sight propagation so that one or more system metrics are generated based on the time varying channel realization sequence.

2. The method of simulating a propagation channel according to claim 1, wherein said obtaining channel power angular distribution additionally comprises:

selecting a channel scenario such that one or more channel parameters are defined according to a channel model;

loading corresponding azimuth parameters to generate azimuth power angular distribution;

providing corresponding elevation parameters to generate elevation power angular distribution; and

computing said channel power angular distribution.

3. The method of simulating a propagation channel according to claim 1, wherein said obtaining channel power angular distribution additionally comprises:

conducting channel probing; and

performing estimation algorithm to obtain said channel power angular distribution.

4. The method of simulating a propagation channel according to claim 1, wherein said generating time-varying channel realization sequence additionally comprises:

forming one or more rays for one or more clusters according to channel power angular distribution;

selecting a transmitting-receiving cluster pair according to a cluster mapping matrix; and

computing channel realizations of multiple channel taps and multiple antenna pairs for a series of time instances.

5. The method of simulating a propagation channel according to claim 1, wherein the time-varying realization sequence is generated to determine one or more system metrics which are selected from a group of system metrics consisting of capacity, Bit Error Rate and Frame Error Rate indicator.

6. A method of evaluating and optimizing antenna design, comprising:

defining one or more antenna structure and material parameters as a population of genetic algorithm;

generating one or more antenna characteristics by one or more electromagnetic computational methods;

computing one or more system metrics by a channel simulator through which one or more receiving clusters are identified at a receiving side of the propagation channel and one or more transmitting clusters are identified at a transmitting side of the propagation channel to map the power relationship between the receiving clusters and the transmitting clusters;

choosing a fitness function as the one or more system metrics to generate a new population; and

obtaining one or more optimized antenna structure and material parameters.

7. The method of evaluating and optimizing antenna design as claimed in claim 6, wherein said antenna characteristics are selected from a group of antenna characteristics consisting of antenna radiation pattern, transmission characteristics, and reflection characteristics.

8. The method of evaluating and optimizing antenna design as claimed in claim 7, wherein said transmission characteristics are selected from a group of transmission characteristics consisting of antenna gain, insertion loss, and MIMO antenna element isolation.

9. The method of evaluating and optimizing antenna design as claimed in claim 7, wherein said reflection characteristics are selected from a group of reflection characteristics consisting of reflection coefficient, return loss, and Voltage Standing Wave Ratio.

10. The method of evaluating and optimizing antenna design as claimed in claim 6, wherein said system metrics are selected from a group of system metrics consisting of ergodic capacity, outage capacity, signal-to-interference-noise ratio (SINR), post-detection SINR, raw symbol error rate, raw bit error rate, coded bit error rate, and frame error rate.

11. The method of evaluating and optimizing antenna design as claimed in claim 6, wherein the antenna is a MIMO antenna.