We consider a general multiple antenna network with multiple sources, multiple destinations and multiple relays in terms of the diversity-multiplexing tradeoff (DMT). We examine several subcases of this most general problem taking into account the processing capability of the relays (half-duplex or full-duplex), and the network geometry (clustered or non-clustered). We first study the multiple antenna relay channel with a full-duplex relay to understand the effect of increased degrees of freedom in the direct link. We find DMT upper bounds and investigate the achievable performance of decode-and-forward (DF), and compress-and-forward (CF) protocols. Our results suggest that while DF is DMT optimal when all terminals have one antenna each, it may not maintain its good performance when the degrees of freedom in the direct link is increased, whereas CF continues to perform optimally. We also study the multiple antenna relay channel with a half-duplex relay. We show that the half-duplex DMT behavior can significantly be different from the full-duplex case. We find that CF is DMT optimal for half-duplex relaying as well, and is the first protocol known to achieve the half-duplex relay DMT. We next study the multiple-access relay channel (MARC) DMT. Finally, we investigate a system with a single source-destination pair and multiple relays, each node with a single antenna, and show that even under the idealistic assumption of full-duplex relays and a clustered network, this virtual multi-input multi-output (MIMO) system can never fully mimic a real MIMO DMT. For cooperative systems with multiple sources and multiple destinations the same limitation remains to be in effect.
The multiple-access relay channel ( ) is introduced in @cite_43 @cite_0 @cite_39 . In , the relay helps multiple sources simultaneously to reach a common destination. The for the half-duplex with single antenna nodes is studied in @cite_31 @cite_37 @cite_34 . In @cite_31 , the authors find that is optimal for low multiplexing gains; however, this protocol remains to be suboptimal for high multiplexing gains analogous to the single-source relay channel. This region, where is suboptimal, is achieved by the multiple access amplify and forward ( ) protocol @cite_37 @cite_34 .
@cite_37 @cite_39 @cite_0 @cite_43 @cite_31 @cite_34
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This paper studies the diversity-multiplexing trade-off for the multiaccess relay channel (MARC) with static, flat fading. It develops two simple strategies, namely multiaccess amplify-and-forward (MAF) and multiaccess decode-and-forward (MDF), that help the users gain the benefit of cooperative diversity without changes in their devices. Results suggest that in the regime of light system loads, both strategies offer improved performance to each user as if no other users interfere or contend for the relay. However, they are inferior to the optimal dynamic decode forward (DDF) protocol in this regime. In the regime of heavy loads, the MARC with MAF offers better performance, and MARC with MDF degenerates into the multiaccess channel (MAC) without a relay. Moreover, the MAF protocol is optimal in the regime of high multiplexing. A three-tier hierarchical wireless sensor network is considered that consists of a cluster of sensors, an intermediate relay with better computing and communication capabilities than the sensors, and a central server or access point. Such a network can be modeled as a multiple-access relay channel (MARC) with additive white Gaussian noise and fading. Capacity bounds for this network are presented with and without constraints on simultaneous reception and transmission by the relay. The results identify cooperative strategies between the relay and sensors for increasing network capacity. These strategies also preserve limited battery resources by eliminating the need for cooperation between sensors. Coding strategies that exploit node cooperation are developed for relay networks. Two basic schemes are studied: the relays decode-and-forward the source message to the destination, or they compress-and-forward their channel outputs to the destination. The decode-and-forward scheme is a variant of multihopping, but in addition to having the relays successively decode the message, the transmitters cooperate and each receiver uses several or all of its past channel output blocks to decode. For the compress-and-forward scheme, the relays take advantage of the statistical dependence between their channel outputs and the destination's channel output. The strategies are applied to wireless channels, and it is shown that decode-and-forward achieves the ergodic capacity with phase fading if phase information is available only locally, and if the relays are near the source node. The ergodic capacity coincides with the rate of a distributed antenna array with full cooperation even though the transmitting antennas are not colocated. The capacity results generalize broadly, including to multiantenna transmission with Rayleigh fading, single-bounce fading, certain quasi-static fading problems, cases where partial channel knowledge is available at the transmitters, and cases where local user cooperation is permitted. The results further extend to multisource and multidestination networks such as multiaccess and broadcast relay channels. In this correspondence, the performance of the automatic repeat request-dynamic decode and forward (ARQ-DDF) cooperation protocol is analyzed in two distinct scenarios. The first scenario is the multiple access relay channel where a single relay is dedicated to simultaneously help two multiple access users. For this setup, it is shown that the ARQ-DDF protocol achieves the channel's optimal diversity multiplexing tradeoff (DMT). The second scenario is the cooperative vector multiple access channel where two users cooperate in delivering their messages to a destination equipped with two receiving antennas. For this setup, a new variant of the ARQ-DDF protocol is developed where the two users are purposefully instructed not to cooperate in the first round of transmission. Lower and upper bounds on the achievable DMT are then derived. These bounds are shown to converge to the optimal tradeoff as the number of transmission rounds increases.