Experimental evaluation of interference alignment for broadband WLAN systems

Abstract

In this paper, we present an experimental study on the performance of spatial interference alignment (IA) in indoor wireless local area network scenarios that use orthogonal frequency division multiplexing (OFDM) according to the physical-layer specifications of the IEEE 802.11a standard. Experiments have been carried out using a wireless network testbed capable of implementing a 3-user MIMO interference channel. We have implemented IA decoding schemes that can be designed according to distinct criteria (e.g., zero-forcing or MaxSINR). The measurement methodology has been validated considering practical issues like the number of OFDM training symbols used for channel estimation or feedback time. In case of asynchronous users, a time-domain IA decoding filter is also compared to its frequencydomain counterpart. We also evaluated the performance of IA from bit error ratio measurement-based results in comparison to different time-division multiple access transmission schemes. The comparison includes single-and multiple-antenna systems transmitting over the dominant mode of the MIMO channel. Our results indicate that spatial IA is suitable for practical indoor scenarios in which wireless channels often exhibit relatively large coherence times.

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“…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.…”

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“…Interference Alignment (IA) can effectively solve the interference problem in the interference channel and increase the achievable sum rate of the channel [ 21 , 22 ]. However, it requires global CSI to design the interference suppression matrix, usually using the feedback of the receiver to inform the CSI required by the transmitter [ 23 , 24 ].…”

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“…However, because of time-varying wireless channel quality, the observation period should not exceed the fluctuation periodicity of the SINR in time domain. According to a recent study [54], the minimum and mean SINR fluctuation periods (for fixed users operating in outdoor environment) are equal 7 and 25 ms, respectively. Consequently, we can choose any value of T, such that 7 ≤ T ≤ 25.…”