This paper proposes interference mitigation techniques for provisioning ultrareliable low-latency wireless communication in an industrial automation setting, where multiple transmissions from controllers to actuators interfere with each other. Channel fading and interference are key impairments in wireless communication. This paper leverages the recently proposed “Occupy CoW” protocol that efficiently exploits the broadcast opportunity and spatial diversity through a two-hop cooperative communication strategy among distributed receivers to combat deep fading, but points out that because this protocol avoids interference by frequency division orthogonal transmission, it is not scalable in terms of bandwidth required for achieving ultrareliability, when multiple controllers simultaneously communicate with multiple actuators (akin to the downlink of a multicell network). The main observation of this paper is that full frequency reuse in the first phase, together with successive decoding and cancellation of interference, can improve the performance of this strategy notably. We propose two protocols depending on whether interference cancellation or avoidance is implemented in the second phase, and show that both outperform Occupy CoW in terms of the required bandwidth and power for achieving ultrareliability at practical values of the transmit power.

This paper studies the effectiveness of relaying for interference mitigation in an interference-limited communication scenario. We are motivated by the observation that in a cellular network, a relay node placed at the cell edge observes a combination of intended signal and inter-cell interference that is correlated with the received signal at a nearby destination, so a relaying link can effectively allow the antennas at the relay and at the destination to be pooled together for both signal enhancement and interference mitigation. We model this scenario by a multiple-input multiple-output (MIMO) Gaussian relay channel with a digital relay-to-destination link of finite capacity, and with correlated noise across the relay and destination antennas. Assuming a compress-and-forward strategy with Gaussian input distribution and quantization noise, we propose a coordinate ascent algorithm for obtaining a stationary point of the non-convex joint optimization of the transmit and quantization covariance matrices. For fixed input distribution, the globally optimum quantization noise covariance matrix can be found in closed-form using a transformation for the relay's observation that simultaneously diagonalizes two conditional covariance matrices by congruence. For fixed quantization, the globally optimum transmit covariance matrix can be found via convex optimization. This paper further shows that such an optimized achievable rate is within a constant additive gap of the MIMO relay channel capacity. The optimal structure of the quantization noise covariance enables a characterization of the slope of the achievable rate as a function of the relaying link capacity. Moreover, this paper shows that the improvement in spatial degrees of freedom by MIMO relaying in the presence of noise correlation is related to the aforementioned slope via a connection to the deterministic relay channel.

This paper explores the benefits of deploying multi-antenna half-duplex amplify-and-forward shared relays at the cell-edge to assist the downlink transmission in a multiple-input multiple-output wireless cellular network. We design the relay node to provide extra spatial dimensions to multiple receivers at the same time for interference mitigation and signal enhancement. This paper proposes an efficient algorithm to solve the non-convex problem of jointly optimizing the transmit beamforming and relay combining matrices to a stationary point by extending the celebrated weighted minimum mean squared error (WMMSE) algorithm. We show that the optimized relaying strategy can significantly improve the long-term average rates of cell-edge users in a cellular network, even after accounting for the extra bandwidth required for halfduplex relaying.

This paper considers a novel use of device-to-device link for cooperative communication wherein a nearby user terminal acts as a relay in enabling both signal enhancement and common interference rejection at the intended destination. Assuming Gaussian transmission and Gaussian compress-and-forward relaying strategy for the multiple-input multiple-output (MIMO) relay channel with a finite-capacity out-of-band relay-destination link and with arbitrarily correlated noises, this paper proposes a coordinate ascent approach for iteratively optimizing the transmit covariance matrix at the source and the quantization noise covariance matrix at the relay. We show that the optimization of quantization noise covariance matrix under fixed input can be solved in closed form using a simultaneous diagonalization approach, while the optimization of transmit covariance matrix under fixed quantization can be cast as a convex optimization problem. This paper further introduces the concept of antenna pooling and illustrates the importance of accounting for the noise correlation across the user terminals due to common interference. We show that the optimized transmission and device-to-device relaying strategies that take advantage of the noise correlation can significantly improve the user throughput in a cellular environment by enabling interference rejection across the user terminals.