Randa Zakhour

Cooperative Multicell Precoding: Rate Region Characterization and Distributed Strategies With Instantaneous and Statistical CSI

Base station cooperation is an attractive way of increasing the spectral efficiency in multiantenna communication. By serving each terminal through several base stations in a given area, intercell interference can be coordinated and higher performance achieved, especially for terminals at cell edges. Most previous work in the area has assumed that base stations have common knowledge of both data dedicated to all terminals and full or partial channel state information (CSI) of all links. Herein, we analyze the case of distributed cooperation where each base station has only local CSI, either instantaneous or statistical. In the case of instantaneous CSI, the beamforming vectors that can attain the outer boundary of the achievable rate region are characterized for an arbitrary number of multiantenna transmitters and single-antenna receivers. This characterization only requires local CSI and justifies distributed precoding design based on a novel virtual signal-to-interference noise ratio (SINR) framework, which can handle an arbitrary SNR and achieves the optimal multiplexing gain. The local power allocation between terminals is solved heuristically. Conceptually, analogous results for the achievable rate region characterization and precoding design are derived in the case of local statistical CSI. The benefits of distributed cooperative transmission are illustrated numerically, and it is shown that most of the performance with centralized cooperation can be obtained using only local CSI.

Multi-Pair Two-Way Relay Channel with Multiple Antenna Relay Station

We consider a multi-pair two-way relay channel (TWRC) where the single-antenna mobile terminals (MT) on each pair seek to communicate, and can do so, via a common multiple antenna relay station (RS). In the multi-pair TWRC, the main bottleneck on system performance is the interference seen by each MT due to the other communicating MT pairs. In this paper, we try to tackle this problem in the spatial domain by using multiple antennas at the RS. Considering Amplify-and-Forward (AF) and Quantize-and-Forward (QF) relaying strategies, different transmit/receive beamforming schemes at the RS are proposed. We compare our proposed schemes to each other and to the Decode-and-Forward (DF) relaying strategy with achievable sum rate taken as a performance metric and show that in a wide range of signal-to-noise ratio (SNR) our schemes outperform the DF relaying strategy.

Distributed Multicell-MISO Precoding Using the Layered Virtual SINR Framework

In this letter, we address the problem of distributed multi-antenna cooperative transmission in a cellular system. Most research in this area has so far assumed that base stations not only have the data dedicated to all the users but also share the full channel state information (CSI). In what follows, we assume that each base station (BS) only has local CSI knowledge. We propose a suboptimal, yet efficient, way in which the multicell MISO precoders may be designed at each BS in a distributed manner, as a superposition of so-called virtual SINR maximizations: a virtual SINR maximizing transmission scheme yields Pareto optimal rates for the MISO Interference Channel (IC); its extension to the multicell MISO channel is shown to provide a distributed precoding scheme achieving a certain fairness optimality for the two link case. We illustrate the performance of our algorithm through Monte Carlo simulations.

A Two-Stage Approach to Feedback Design in Multi-User MIMO Channels with Limited Channel State Information

We consider the downlink of a multiuser MIMO channel, corresponding to a single cell with an Nt-antenna base station and K single-antenna mobile terminals (MTs). It is known that when full channel state information (CSI) is available at the transmitter (full CSIT) the capacity of the system scales as Nt log(P/Nt- log K), under a total power constraint P [1], While, when the transmitter has no CSI, scaling reduces to that of a TDMA system. This paper examines the more realistic case of having an intermediate state of CSI. The key idea is based on a split of the allotted feedback between two stages: A first stage devoted to scheduling followed by a second stage for precoder design for the selected users. Based on an approximation of the achievable sum rate, we introduce a method for determining the splitting of the feedback rate so as to maximize performance and provide intuitions. We illustrate the gains of the 2-stage approach via Monte Carlo simulations.

Distributed Multicell and Multiantenna Precoding: Characterization and Performance Evaluation

This paper considers downlink multiantenna communication with base stations that perform cooperative precoding in a distributed fashion. Most previous work in the area has assumed that transmitters have common knowledge of both data symbols of all users and full or partial channel state information (CSI). Herein, we assume that each base station only has local CSI, either instantaneous or statistical. For the case of instantaneous CSI, a parametrization of the beamforming vectors used to achieve the outer boundary of the achievable rate region is obtained for two multi-antenna transmitters and two single-antenna receivers. Distributed generalizations of classical beamforming approaches that satisfy this parametrization are provided, and it is shown how the distributed precoding design can be improved using the so-called virtual SINR framework [1]. Conceptually analog results for both the parametrization and the beamforming design are derived in the case of local statistical CSI. Heuristics on the distributed power allocation are provided in both cases, and the performance is illustrated numerically.

Team decision for the cooperative MIMO channel with imperfect CSIT sharing

We consider the problem of joint MIMO precoding across multiple distant cooperating transmitters. The transmitters are assumed to be sharing user data and aim at serving a group of users in a distributed MIMO broadcast-like fashion. Among application scenarios, we find the so-called network MIMO setup. The novelty of our setup resides in the fact that each of the transmitters obtains imperfect and importantly, different, estimates of the same global multi-user channel. Despite not sharing the same vision over the CSIT, the transmitters seek to jointly act in a consistent manner in designing the precoders. This problem in facts falls in the class of so-called Team Decision Theory problems. We present some solutions to the problem of beamforming design in this case and illustrate the benefits in practical network scenarios.

Adaptive feedback rate control in MIMO broadcast systems

We consider a MIMO broadcast channel where the channel state information at the transmitter (CSIT), to be used for user scheduling and beamforming, is gained through a limited-rate feedback channel. In view of optimizing the overall spectral efficiency of the system, we propose an adaptive scheme in which the feedback rate is no longer constant but rather optimized as a function of the time-dependent channel quality seen at the user side. One key idea is that, under an average feedback rate constraint, a user ought to provide more feedback at moments when it is more likely to be scheduled.We provide the theoretical grounds for our approach then derive quasi-optimal feedback resource allocation schemes, the performance of which is illustrated through Monte Carlo simulations.