MIMO communication may provide high spectral efficiency through the deployment of a very large number of antenna elements at the base stations. The gains from massive MIMO communication come from the use of multi-user MIMO on the uplink and downlink, but with a large excess of antennas at the base station compared to the number of served users. Initial work on massive MIMO did not fully address several practical issues associated with its deployment. This paper considers the impact of channel aging on the performance of massive MIMO systems. The effects of channel variation are characterized as a function of different system parameters assuming a simple model for the channel time variations at the transmitter. Channel prediction is proposed to overcome channel aging effects. The analytical results on aging show how capacity is lost due to time variation in the channel. Numerical results in a multicell network show that massive MIMO works even with some channel variation and that channel prediction could partially overcome channel aging effects.

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Interference alignment is a signaling technique that provides high multiplexing gain in the interference channel. It can be extended to multi-hop interference channels, where relays aid transmission between sources and destinations. In addition to coverage extension and capacity enhancement, relays increase the multiplexing gain in the interference channel. In this paper, three cooperative algorithms are proposed for a multiple-antenna amplify-and-forward (AF) relay interference channel. The algorithms design the transmitters and relays so that interference at the receivers can be aligned and canceled. The first algorithm minimizes the sum power of enhanced noise from the relays and interference at the receivers. The second and third algorithms rely on a connection between mean square error and mutual information to solve the end-to-end sum-rate maximization problem with either equality or inequality power constraints via matrix-weighted sum mean square error minimization. The resulting iterative algorithms converge to stationary points of the corresponding optimization problems. Simulations show that the proposed algorithms achieve higher end-to-end sum-rates and multiplexing gains that existing strategies for AF relays, decode-and-forward relays, and direct transmission. The first algorithm outperforms the other algorithms at high signal-to-noise ratio (SNR) but performs worse than them at low SNR. Thanks to power control, the third algorithm outperforms the second algorithm at the cost of overhead.Comment: submitted to IEEE Transactions on Signal Processing in December 2011, revised in April 2012 and in September 201

This paper considers a multi-user simultaneous wireless information and power transfer (SWIPT) system with a non-linear energy harvesting model, in which a multi-antenna base station (BS) estimates the downlink channel state information (CSI) via uplink pilots. Each single-antenna user is equipped with a power splitter. Three crucial issues on resource management for this system include: (i) power-efficient improvement, (ii) user-fairness guarantee, and (iii) non-ideal channel reciprocity effect mitigation. Potentially, a resource allocation scheme to address jointly such issues can be devised by using the framework of multi-objective optimization. However, the resulting problem might be complex to solve since the three issues hold different characteristics. Therefore, we propose a novel method to design the resource allocation scheme. In particular, the principle of our method relies on structuralizing mathematically the issues into a cross-layer multi-level optimization problem. On this basis, we then devise solving algorithms and closed-form solutions. Moreover, to instantly adapt the CSI changes in practice while reducing computational burdens, we propose a closed-form suboptimal solution to tackle the problem. Finally, we provide numerical results to show the achievable performance gains using the optimal and suboptimal solutions, and then validate the proposed resource allocation scheme.Index Terms-Energy harvesting, simultaneous wireless information and power transfer, resource allocation.

The transmission capacity of an ad-hoc network is the maximum density of active transmitters per unit area, given an outage constraint at each receiver for a fixed rate of transmission. Most prior work on finding the transmission capacity of ad-hoc networks has focused only on one-way communication where a source communicates with a destination and no data is sent from the destination to the source. In practice, however, two-way or bidirectional data transmission is required to support control functions like packet acknowledgements and channel feedback. This paper extends the concept of transmission capacity to two-way wireless ad-hoc networks by incorporating the concept of a two-way outage with different rate requirements in both directions. Tight upper and lower bounds on the two-way transmission capacity are derived for frequency division duplexing. The derived bounds are used to derive the optimal solution for bidirectional bandwidth allocation that maximizes the two-way transmission capacity, which is shown to perform better than allocating bandwidth proportional to the desired rate in both directions. Using the proposed two-way transmission capacity framework, a lower bound on the two-way transmission