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DFT-Based Vs. Cooperative MET-Based MU-MIMO in the Downlink of Cellular OFDM Systems

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DFT-Based Vs. Cooperative MET-Based MU-MIMO in the Downlink of Cellular OFDM Systems 2009 International ITG Workshop on Smart Antennas { WSA 2009, February 16{18, Berlin, Germany DFT-based vs. Cooperative MET-based MU-MIMO in the Downlink of Cellular OFDM Systems L. Thiele, M. Schellmann, T. Wirth and V. Jungnickel F. Boccardi and H. Huang Fraunhofer Institute for Telecommunications Bell Labs, Heinrich-Hertz-Institut Alcatel-lucent Einsteinufer 37, 10587 Berlin, Germany fb,hchuang @alcatel-lucent.com { } thiele, schellmann, thomas.wirth, jungnickel @hhi.fraunhofer.de { } Abstract—In this work, we compare different pre-coding tech- work, we include multi-user selection diversity in the user niques and their performance in a cellular MIMO OFDM down- grouping process. Multi-user diversity from a large number link. The first target is to determine the achievable additional of users per cell may help to increase the system performance beamforming gain by using a near-optium pre-coder instead of DFT-based pre-coding. In the second step, we include multi-user further. From [2] it is well known that this would require a selection diversity, which turned out to be advantageous especially brute force or at least a greedy search over the user space for downlink cooperation. An extended score-based scheduler, to choose appropriate users for the active set . To combat M which is known to asymptotically reach proportional fairness, residual CCI from surrounding cells we employ MMSE equal- is used for the user grouping and resource allocation in the ization, also known as optimum combining (OC) [4], at the cellular downlink. Further, we use minimum mean square error equalization at the terminal side to combat residual cochannel terminal side. interference. II. DOWNLINK SYSTEM MODEL NTRODUCTION I. I The downlink MIMO-OFDM transmission system with NT To enable ubiquitous broadband wireless access in fu- transmit and NR receive antennas per MT is described on each ture cellular systems supporting multiple-input multiple-output subcarrier by (MIMO) technology, transmission must be made robust against y = HCx + n , (1) multi-cell interference. Recently, it was shown that the capac- where H is the N N channel matrix and C the unitary ity scaling law, known from an isolated cell, also holds for R × T N N pre-coding matrix; x denotes the N 1 vector the interference limited case of a multi-cellular radio system T × T T × of transmit symbols; y and n denote the NR 1 vectors [1] with NT = NR transmit and receive antennas. This × work mainly focused on the optimization at the receiver side. of the received signals and of the additive white Gaus- However, cochannel interference (CCI) is still the dominant sian noise (AWGN) samples, respectively, with covariance E nnH = σ2I. source of performance degradation in the cellular network, { } α especially if N > N . Removing CCI may lead to a Assume that a group of cooperating base station (BS) T R C αN additional performance gain. sectors provides a beam set i. The beam set contains T b u 1, ..., αN In this work we compare different pre-coding techniques pre-coding beams i,u with T . In the follow- b u ∈ { } and their performance in a cellular MIMO orthogonal fre- ing we denote i,u as the -th pre-coding vector provided by i ym quency division multiplexing (OFDM) downlink. As a baseline the -th cell cluster. The received downlink signal at the m concept, we consider independent DFT-based pre-coding and MT in the cellular environment is given by multi-user MIMO (MU-MIMO) service in each sector of αNT m m m the system. As a first target, we determine the available y = Hi bi,u xi,u + Hi bi,jxi,j additional beamforming gain by using a near-optium pre- j=1 h jX=u coder instead. Therefore, we employ multi-user eigenmode i,u 6 transmission (MET), known to realize 90% of the dirty paper | {z } ζi,u coding (DPC) capacity in an isolated cell context [2], based NT m| {z } on the dominant eigenmodes of the mobile terminals (MTs) + Hl bl,jxl,j + n , (2) l j=1 in the serving area. Xl∀=i X A second target of this work is to realize limited localized 6 cooperative transmission in a multi-cellular network. Recent zi,u results obtained for a cellular MIMO OFDM downlink with a The desired data stream| xi,u transmitted{z on} the u-th beam sparse user distribution per sector, show potential performance from the i-th cluster is distorted by the intra-cluster and inter- gains for cooperation [3]. In this context it turned out, that cluster interference aggregated in ζi,u and zi,u, respectively. downlink cooperation based on DFT beams is unsuitable and Hm spans the N αN channel matrix for user m formed by i R× T MET should get the precedence. Additionally to preceding the cluster i. Thus, ζi,u denotes the interference generated in 2009 International ITG Workshop on Smart Antennas { WSA 2009, February 16{18, Berlin, Germany the cooperation area. In the scope of this paper, it is assumed that all αNT beams in the beam set Ci are simultaneously ac- tive, whereby the total available power pi is assumed to be uni- formly distributed over the αN beams. Thus, E x 2 = T | i,j| p /(αN ) holds, and p = αNT E x 2 = αp with p i T i j=1 | i,j| s s being the transmit power per sector. P A. Determine serving BS or cooperative BS cluster The general assumption for single-cell operation is that each MT is assigned to the BS sector yielding the highest receive power over the entire frequency band, which is denoted as top-1 signal. Thus, the BS assignment is based on broadband Fig. 1. System concept assuming multiple antennas at the base station for power conditions, and a fast cell handover is assumed. For the purpose unitary fixed DFT-based pre-coded beamforming. SINR feedback downlink cooperation, we extend this scheme by evaluating is provided by the terminal for possible transmission modes using a narrow the top-α strongest signals and grouping the users selecting band feedback channel. the same set of α BSs for joint signal transmission. By subdividing the signal bandwidth into single sub-bands dominant eigenmodes of their channel to the cell cluster confined to a fixed number of consecutive subcarriers, we together with the corresponding eigenvalues. MET supports to define sets of contiguous transmission resources, which are simultaneously transmit up to αNT data streams via unitary denoted as resource blocks (RBs) in the following. Each RB precoding beams, while up to NR beams may be assigned is processed independently, and thus the sectors to form a to a single MT. However, it has been indicated in [2] that group for cooperation can be selected individually per RB. MU-MIMO service for distinct terminals using MET is more III. DOWNLINK PRE-CODING efficient than time-multiplexing multi-stream transmission to a single user. Thus, for our investigations, we let all MTs A. Baseline: DFT-based fixed pre-coding report their dominant eigenmode only (λ = 1), which keeps As a baseline, we consider a system concept from [1], the required amount of feedback per user limited. where all sectors operate independently, while the inter- Determination of the MET-based pre-coding beams in ma- cell interference is accounted for at the multi-antenna MTs trix C is briefly sketched as follows: Consider a fixed set M only. The following evaluation is carried out for each RB of users, which should be served in a RB. Each user m decom- independently (refer to Fig. 1): Each BS provides a fixed m poses its NR αNT channel matrix Hi according to the sin- matrix C consisting of unitary DFT beams. Assuming that × m H gular value decomposition (SVD), yielding Hi = UiΣiVi . the inter-cell interference is completely known at the MTs, The dominant eigenmode is the first column vector of matrix the MTs evaluate the achievable rate per beam and convey Vi, denoted as vi,1. Together with the dominant eigenvalue in this information to their BS. At the BS, the feedback from the Σi, denoted as Σi,1, we obtain the user’s effective eigenmode different MTs is collected, and the DFT beams from matrix C H channel Γm = Σi,1vi,1. This measure needs to be fed back are assigned individually to the MTs. This simple approach has from each MT to the cell cluster. the convenient property that with the fixed beam set C used User orthogonalization at the BS: To obtain the pre-coding for all BSs, the CCI, i.e. ζi,u +zi,u, becomes fully predictable, vector for the m-th user, the BS cluster aggregates the interfer- enabling interference-aware scheduling in a cellular system. ing eigenmodes Γ with n 1, ..., (m 1), (m+1), ..., αN n ∈ { − T } In combination with fair, interference-aware scheduling from the other terminals in the active set , yielding a matrix M policies, it has been shown that users profit from almost of dimension (αNT 1) αNT doubled spectral efficiencies in the MIMO 2 2 system, as − × × ˜ H H H H H compared to the single-input single-output (SISO) setup [1]. Γm = [Γ1 ... Γm 1 Γm+1 ... ΓαNT ] (3) − ˜ B. Downlink cooperation: MET-based pre-coding Performing the SVD of Γm yields There are several concepts for cooperative downlink trans- ˜ ˜ 1 0 H Γm = Um Σ˜ m 0 V˜ v˜ , (4) mission, all imposing different demands on the system archi- m m 0 tecture. As a basic requirement, coherent downlink transmis- where v˜m corresponds to the eigenvector associated with sion is mandatory.
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