Receive Soft Antenna Selection for Noise-Limited/Interference MIMO Channels

Although the Multi-Input and Multi-Output (MIMO) communication systems provide very high data rates with low error probabilities, these advantages are obtained at the expense of having high signal processing tasks and the hardware cost, e.g. expensive Analog-to-Digital (A/D) converters. The increased hardware cost is mainly due to having multiple Radio Frequency (RF) chains (one for each antenna element). Antenna selection techniques have been proposed to lower the number of RF chains and provide a low cost MIMO system. Among them, due to a beamforming capability Soft Antenna Selection (SAS) schemes have shown a great performance improvement against the traditional antenna sub-set selection methods for the MIMO communication systems with the same number of RF chains. A SAS method is basically realized by a pre-processing module which is located in RF domain of a MIMO system. In this thesis, we investigate on the receive SAS-MIMO, i.e. a MIMO system equipped with a SAS module at the receiver side, in noise-limited/interference channels. For a noise-limited channel, we study the SAS-MIMO system for when the SAS module is implemented before Low Noise Amplifier (LNA), so-called pre-LNA, under both spatial multiplexing and diversity transmission strategies. The pre-LNA SAS module only consists of passive elements. The optimality of the pre-LNA SAS method is investigated under two di erent practical cases of either the external or internal noise dominates. For the interference channel case, the post-LNA SAS scheme is optimized based on Power Angular Spectrum (PAS) of the received interference signals. The analytical derivations for both noise-limited and interference channels are verified via the computer simulations based on a general Rician statistical MIMO channel model. The simulation results reveal a superiority of the post-LNA SAS to the post-LNA SAS at any condition. Moreover, using the simulations performed for the interference channels we show that the post-LNA SAS is upper bounded by the full-complexity MIMO. Since in both above-mentioned channels, noise-limited and interference, the channel knowledge is needed for the SAS optimization, in this thesis we also propose a two-step channel estimation method for the SAS-MIMO. This channel estimation is based on an Orthogonal Frequency-Division Multiplexing (OFDM) MIMO system. Two di erent estimators of Least-Square (LS) and Minimum-Mean-Square- Error (MMSE) are applied. Simulation results show a superiority of the MMSE method to the LS estimator for a MIMO system simulated under the 802.16 framing strategy. Moreover, a 802.11a framing based SAS-MIMO is simulated using MATLAB SIMULINK to verify the two-step estimation procedure. Furthermore, we also employ a ray-tracing channel simulation to assess di erent SAS configurations, i.e. realized by active (post-LNA) and/or passive (pre-LNA) phased array, in terms of signal coverage. In this regard, a rigorous Signal to Noise Ratio (SNR) analysis is performed for each of these SAS realizations. The results show that although the SAS method performance is generally said to be upperbounded by a full-complexity MIMO, it shows a better signal coverage than the full-complexity MIMO

ASCCC Fractal and Its Application in Antenna Miniaturization

In this chapter, ASCCC fractal is defined. The name “ASCCC” is based on the process that the fractal is built. It is made by adding and subtracting circles to the circumference of a circle. Then the necessary formulas to build up the first and higher orders of ASCCC fractal are derived. By calculating the perimeter of each order, it is shown that the ASCCC fractal has a great capability in antenna miniaturization. Based on first-order ASCCC fractal, a systematic approach is designed to miniaturize an antipodal dipole at any arbitrary frequency. Then the proposed method is applied at band LTE13 (746–787 MHz), which is controversy for mobile antenna, because it causes the size of a common antenna to become very large for a handheld mobile. It is illustrated that not only the ASCCC fractal is successful in miniaturization of dipole antenna, but also it is very good at improving the antenna’s efficiency in comparison with its counterparts like Koch dipole/monopole

Dynamic Range Consideration in MIMO Systems with Hybrid Antenna Selection

A Hybrid Antenna Selection (HAS), also called Soft Antenna Selection (SAS), method is basically implemented by a Linear Network (LN) located in RF domain of Multiple Input Multiple Output (MIMO) systems. In this paper, we evaluate the SAS-MIMO system, which is optimally tuned based on spatial multiplexing/diversity transmissions, in terms of receiver dynamic range issue. To this end, an SNR analysis is first performed for a reference point that is the input of Receiver Chain Block (RCB). Different systems are then compared based on a standard receiver, that is, WLAN 802.11 b. A three Dimensional (3D) ray-tracing modeling is applied to assist this evaluation. The simulation results for a case study show that although the optimum post-LNA SAS works like a full-complexity MIMO in the spatial multiplexing/diversity transmission strategies, it provides even a better SNR to the baseband, that is, it reveals a receiver dynamic range improvement

Sampling Rate Reduction for 60 GHz UWB Communication using Compressive Sensing

Abstract — 60 GHz ultra wide-band (UWB) communication is an emerging technology for high speed short range communications. However, the challenge of high speed sampling increases the cost of receiver circuitry such as analog-to-digital converter (ADC). In this paper, we propose the utilization of compressive sensing frame work to achieve great reduction of sampling rate. The basic idea is based on the observation that the received signals are sparse in the time domain due to the limited multipath effects at 60 GHz wireless transmission. According to the compressive sensing theory, by carefully designing the sensing scheme, sub-Nyquist rate sampling of the sparse signal still enables exact recovery with overwhelming probability. In the proposed scheme, we offers prototype implementation of low speed A/D conversion for 60 GHz UWB received signal. Moreover, we analyze the bit error rate (BER) performance for BPSK modulation under RAKE reception. Simulation results show that in the single antenna pair system model, sampling rate can be reduced to 2.2 % with 0.3dB loss of BER performance if the input sparsity is less than 1%. Consequently, the implementation cost of ADC is significantly reduced. I