A Practical Cooperative Multicell MIMO-OFDMA Network Based on Rank Coordination

Abstract

Abstract-An important challenge of wireless networks is to boost the cell edge performance and enable multi-stream transmissions to cell edge users. Interference mitigation techniques relying on multiple antennas and coordination among cells are nowadays heavily studied in the literature. Typical strategies in OFDMA networks include coordinated scheduling, beamforming and power control. In this paper, we propose a novel and practical type of coordination for OFDMA downlink networks relying on multiple antennas at the transmitter and the receiver. The transmission ranks, i.e. the number of transmitted streams, and the user scheduling in all cells are jointly optimized in order to maximize a network utility function accounting for fairness among users. A distributed coordinated scheduler motivated by an interference pricing mechanism and relying on a masterslave architecture is introduced. The proposed scheme is operated based on the user report of a recommended rank for the interfering cells accounting for the receiver interference suppression capability. It incurs a very low feedback and backhaul overhead and enables efficient link adaptation. It is moreover robust to channel measurement errors and applicable to both open-loop and closed-loop MIMO operations. A 20% cell edge performance gain over uncoordinated LTE-A system is shown through system level simulations.

An interference-aware distributed transmission technique for dense small cell networks

“…Unfortunately, such an approach requires a central node with global CSI. Moreover, the computational complexity scales exponentially with L, making such a BF approach infeasible for practical systems [10]. A coordinated approach to solving Eq.…”

“…A coordinated approach to solving Eq. (5) motivated by an interference pricing mechanism is introduced in [10]. However, the proposed solution is based on the exchange of interference pricing information and tend to be slow in convergence.…”

Coordinated beamforming design for multicell systems with transceiver impairments: from perspective of spectral efficiency to energy efficiency

“…Coordinated or cooperative beamforming, where multiantenna reprocessing at neighboring base stations (BSs) are designed cooperatively, has been extensively studied in the existing literatures such as [3][4][5][6][7][8][9] and thereof. To be more specific, the transmit power minimization problem subject to signal-to-interference-and-noise-ratio (SINR) constraints at the remote users was addressed based on *Correspondence: huangym@seu.edu.cn 1 School of Information Science and Engineering, Southeast University, Nanjing 210096, China Full list of author information is available at the end of the article the uplink-downlink duality theorem for multicell multiuser downlink systems [3].…”

“…Unlike the aforementioned references where a coordinated beamforming algorithm was designed assuming a fixed coordinated BS cluster, in [5], the authors investigated a novel multicell coordinated beamforming framework with dynamic cooperation clusters where each user is jointly served by a small set of BSs. In [6], the number of transmitted streams and the user scheduling in all cells were jointly optimized in order to maximize a network utility function accounting for fairness among users. Based on a novel virtual SINR framework, a distributed precoding design method which needs only local channel state information (CSI) was proposed for a coordinated joint transmission system [7].…”

Interference Pricing Mechanism for Downlink Multicell Coordinated Beamforming

“…It is in this sense that interference pricing has been recently used for the design of linear beamforming for MIMO links [19], multicell networks [20] and single-cell MIMO systems [21], [22]. A distributed coordinated scheduler relying on a master-slave architecture has been proposed in [23] to optimize the network weighted sum-rate with uniform power allocation and fixed beamformers. Interestingly, the problem is maximized over transmission ranks and user scheduling rather than the usual beamforming vectors.…”