An Overview of Algorithms for Downlink Transmit Beamforming (original) (raw)

Distributed Downlink Beamforming With Cooperative Base Stations

IEEE Transactions on Information Theory, 2008

In this paper, we consider multicell processing on the downlink of a cellular network to accomplish "macrodiversity" transmit beamforming. The particular downlink beamformer structure we consider allows a recasting of the downlink beamforming problem as a virtual linear mean square error (LMMSE) estimation problem. We exploit the structure of the channel and develop distributed beamforming algorithms using local message passing between neighboring base stations. For 1-D networks, we use the Kalman smoothing framework to obtain a forward-backward beamforming algorithm. We also propose a limited extent version of this algorithm that shows that the delay need not grow with the size of the network in practice. For 2-D cellular networks, we remodel the network as a factor graph and present a distributed beamforming algorithm based on the sum-product algorithm. Despite the presence of loops in the factor graph, the algorithm produces optimal results if convergence occurs.

Distributed Beamforming Based on Signal-to Caused-Interference Ratio

2008 IEEE 10th International Symposium on Spread Spectrum Techniques and Applications, 2008

This paper presents a distributed beamforming technique that addresses the effect of inter-cell interference on the downlink of cellular communications systems. The beamforming weights are computed in a distributed manner at each transmit sector antenna array without the need for intersector communication. The beamforming weights are chosen to compromise between maximizing the power to the served user from each sector while minimizing the interference caused to users served in adjacent sectors. The extensions of this method for variable levels of channel state information feedback and multiple receiver antennas are introduced. Beamforming codebooks with power variations across antennas are presented. We show how users can additionally feed back the fraction of interference caused by each interfering sector to incorporate the urgency of interference avoidance into the transmitter optimization.

Transmit beamforming with cooperative base stations

Proceedings. International Symposium on Information Theory, 2005. ISIT 2005., 2005

We consider a cellular network where base stations can cooperate to determine the signals to be transmitted on the downlink. In such a scenario, it would be possible to use "macroscopic" transmit beamforming to improve system performance. The downlink beamformer of interest is generalised from some transmit beamformers that have been shown to meet various optimality criteria in the literature. The particular downlink beamformer structure enables us to recast our downlink beamforming problem as a virtual LMMSE estimation problem. Based on this virtual set up, we exploit the structure of the channel and develop distributed beamforming algorithms using local message passing between neighbouring base stations. Two algorithms are outlined, both of which are based on the Kalman smoothing framework. The first algorithm is a forward-backward algorithm that produces optimal performance, but it has the disadvantage of a delay that grows linearly with array size. The second algorithm, which is a limited extent algorithm, solves the delay problem by using only local information.

Distributed Downlink Beamforming in Cellular Networks

2007 IEEE International Symposium on Information Theory, 2007

We consider a cellular network where base stations can cooperate to determine the signals to be transmitted on the downlink. Using a particular downlink beamformer structure, we recast our downlink beamforming problem as a virtual linear minimum mean square error (LMMSE) estimation problem. Based on this virtual set up, we remodel the network as a factor graph with loops and present a simple distributed cooperative scheme for base stations based on the sum-product algorithm. We study the condition for convergence for the distributed algorithm and demonstrate its performance via simulations.

On Downlink Beamforming Methods: Capacity and Error Probability Performance

Wireless Personal Communications, 2004

In space-division multiple access (SDMA), different beamforming or space-domain precoding techniques can be applied. We investigate two different space-domain precoding methods, the maximum capacity (MC) and the minimum mean square error (MMSE) precoders, for the downlink channel. It is shown that the MMSE precoding, which is practically implementable, can provide a reasonable performance in terms of the capacity and error probability, while the MC precoding is not practical (although it is optimum in terms of the capacity). Space-domain precoding methods are also applied to code-division multiple access (CDMA) systems.

Joint beamforming and transmit diversity for wireless communications

2004 International Conference on Communications, Circuits and Systems (IEEE Cat. No.04EX914)

The current work develops an efficient scheme to be used for the downlink of a WCDMA network, using transmitter diversity and b eamforming. The performances of space-time transmit diversity (STTD) in combination with selective transmit diversity (STD), beamforming (BF) and beam sele ctive transmit diversity (BSTD) which is a composite scheme of STD and BF, have been studied at the system level using the capacity as performance index. Both fading and interference are jointly considered in the multipath propagation environment. The main constraint was the implementation problem. It considers the use of an array with eight antenna elements spaced half wavelength per 120 o sector to implement dynamically the several proposed techniques based on the environment. It was found that the comparison is strongly related to the availability of path diversity. The system capacity is maximized by the BF in the presence of multipath diversity and high multiple access interference. Otherwise it is the BSTD that achieves the best overall capacity performance. For higher data rates and small number of users the system that gives the best capacity performance is STTD+STD.

An introduction to the multi-user MIMO downlink

IEEE Communications Magazine, 2004

Multiple-input multiple-output (MIMO) communication techniques have been an important area of focus for next-generation wireless systems because of their potential for high capacity, increased diversity, and interference suppression. For applications such as wireless LANs and cellular telephony, MIMO systems will likely be deployed in environments where a single base must communicate with many users simultaneously. As a result, the study of multiuser MIMO systems has emerged recently as an important research topic. Such systems have the potential to combine the high capacity achievable with MIMO processing with the benefits of space-division multiple access. In this article we review several algorithms that have been proposed with this goal in mind. We describe two classes of solutions. The first uses a signal processing approach with various types of transmitter beamforming. The second uses "dirty paper" coding to overcome the interference a user sees from signals intended for other users. We conclude by describing future areas of research in multiuser MIMO communications.

System evaluation of optimal downlink beamforming with congestion control in wireless communication

2006

We investigate the use of congestion control and joint optimal downlink beamforming, power control, and access point allocation, in a multi-cell wireless communication system. The access points of the system employ smart antennas and single antennas are used at the terminals. The possibility to send messages to multiple terminals at the same frequency in the same time slot is exploited. We show how previously proposed algorithms for optimal downlink beamforming easily can be extended to determine also the optimal access point for each mobile terminal. In order to assign resources, optimal beamforming requires a feasible set of mobiles, i.e. that all admitted users can be offered the required Signal-to-Interference-and-Noise Ratio. Therefore, an algorithm for deciding which mobile terminals to admit or reject from a congested system is proposed and evaluated. Using the proposed congestion algorithm, joint optimal downlink beamforming is evaluated and the throughput increase as compared to decentralized beamforming algorithms and other congestion control strategies is assessed from a system point of view. The results show that the proposed strategy can almost double the throughput compared to decentralized beamforming algorithms and give a fivefold increase in throughput compared to conventional beamforming without any interference suppression.

Performance Comparison between Beamforming and Spatial Multiplexing for the Downlink in Wireless Cellular Systems

IEEE Transactions on Wireless Communications, 2000

We compare the performance between beamforming and spatial multiplexing showing in which downlink scenarios the higher performance of spatial multiplexing justify its complexity. We compute performance using readily measurable parameters such as angle spread (AS), antenna separation and signal to noise ratio (SNR). Firstly, a semi-analytical approach relates these measurable parameters with parameters that theoretically characterize beamforming optimality such as the spatial correlation matrix first two eigenvalues and SNR. Secondly, the achieved spectral efficiency is given for beamforming and spatial multiplexing as a function of antenna separation, AS and SNR. Also, a "practical" region is given where beamforming achieves at least 90% of the spectral efficiency of spatial multiplexing.