An experimental evaluation of broadband spatial IA for uncoordinated MIMO-OFDM systems

Abstract

In this paper we present an experimental study on the performance of spatial Interference Alignment (IA) in broadband indoor wireless local area network scenarios that use Orthogonal Frequency Division Multiplexing (OFDM) according to the IEEE 802.11a physical-layer specifications. Experiments have been carried out using a wireless network testbed made up of six nodes equipped with Multiple-Input Multiple-Output (MIMO) radio interfaces. This setup allows the implementation of a 3-user MIMO interference channel. We have implemented different IA decoding schemes that operate either before or after the Fast Fourier Transform block. IA has been experimentally evaluated comparing both approaches to analyze its performance in synchronous and asynchronous transmissions. Our results indicate that spatial IA performs satisfactorily in practical broadband indoor scenarios in which wireless channels often exhibit relatively large coherence times.

Experimental evaluation of flexible duplexing in multi-tier MIMO networks

“…However, in real-world systems, detection and synchronization are performed right after the RF demodulation and analog-to-digital conversion, i.e., at sample level, thus they are affected by interference. The pre-FFT IA approach in [29,30] overcomes this issue by operating at sample level, that is, in the time domain. Nevertheless, since the synchronization mismatches have been already studied in the aforementioned works, we rely on an external clock and oscillator for time and frequency synchronization (see Section 3), and apply IA precoders and decoders in the frequency domain.…”

“…As in[29,30], the channel estimates in steps 1 and 4 are obtained by dividing the received long training symbols by the original LT symbols on a per-subcarrier basis.…”

Interference Alignment Testbeds

“…However, an optimal trade-off between network resources dedicated to CSI acquisition and feedback with respect to those devoted to data transmissions must be determined to maximize the throughput [1], [6], [7]. Error vector magnitude (EVM) experimental results for a pilot-assisted maximum signal-to-interference plus noise ratio (max-SINR) scheme corroborate the existence of an optimal resource allocation scheme [7], and an optimal number of training symbols [4]. Time and frequency synchronization between network nodes is of utmost importance when experimentally evaluating IA techniques and it can be implemented in a centralized [8] or a distributed manner [2], [5].…”

“…The CSI acquisition problem is mitigated in time-division duplexing (TDD) systems by exploiting channel reciprocity, although calibrated RF equipment is required [2]. For frequency-division duplexing (FDD) systems, IA experiments with perfect [3], [4] and realistic analog wireless [5] feedback channels have been reported in the literature. Furthermore, in most of the theoretical IA works, the block-fading channel model assumption plays a pivot role due to its mathematical tractability [1].…”

“…The finite signal-to-noise ratio (SNR) at the receiver is another practical limitation. However, experimental results show that, despite the imperfections in both CSI acquisition and testbed hardware, IA outperforms conventional communication schemes such as TDMA and greedy interference avoidance in the mid-to-high SNR regime [4]. However, an optimal trade-off between network resources dedicated to CSI acquisition and feedback with respect to those devoted to data transmissions must be determined to maximize the throughput [1], [6], [7].…”