A clustered base transceiver station (BTS) coordination strategy is proposed for a large cellular MIMO network, which includes full intra-cluster coordination to enhance the sum rate and limited inter-cluster coordination to reduce interference for the cluster edge users. Multi-cell block diagonalization is used to coordinate the transmissions across multiple BTSs in the same cluster. To satisfy per-BTS power constraints, three combined precoder and power allocation algorithms are proposed with different performance and complexity tradeoffs. For inter-cluster coordination, the coordination area is chosen to balance fairness for edge users and the achievable sum rate. It is shown that a small cluster size (about 7 cells) is sufficient to obtain most of the sum rate benefits from clustered coordination while greatly relieving channel feedback requirement. Simulations show that the proposed coordination strategy efficiently reduces interference and provides a considerable sum rate gain for cellular MIMO networks.
Recently, has been proposed as an effective technique to mitigate interference in the downlink of multi-cell networks @cite_15 . By sharing information across BTSs and designing downlink signals cooperatively, signals from other cells may be used to assist the transmission instead of acting as interference, and the available degrees of freedom are fully utilized. In @cite_28 , BTS coordination with DPC was first proposed with single-antenna transmitters and receivers in each cell. BTS coordination in a downlink multi-cell MIMO network was studied in @cite_9 , with a per-BTS power constraint and various joint transmission schemes. The maximum achievable common rate in a coordinated network, with zero-forcing (ZF) and DPC, was studied in @cite_11 @cite_31 , which demonstrated a significant gain over the conventional single BTS transmission. With simplified network models, analytical results were derived for multi-cell ZF beamforming in @cite_34 and for various coordination strategies with grouped cell interior and edge users in @cite_41 . Studies considering practical issues such as limited-capacity backhaul and asynchronous interference can be found in @cite_42 @cite_43 @cite_4 @cite_32 .
@cite_31 @cite_4 @cite_28 @cite_41 @cite_9 @cite_42 @cite_32 @cite_43 @cite_15 @cite_34 @cite_11
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We quantify the ultimate performance limits of inter-cell coordinatation in a cellular downlink network. The goal is to achieve fairness by maximizing the minimum rate in the network subject to per base power constraints. We first solve the max-min rate problem for a particular zero-forcing dirty paper coding scheme so as to obtain an achievable max-min rate, which serves as a lower bound on the ultimate limit. We then obtain a simple upper bound on the max-min rate of any scheme, and show that the rate achievable by the zero-forcing dirty paper coding scheme is close to this upper bound. We also extend our analysis to coordinated networks with multiple antennas. In this contribution we present new achievable rates, for the non-fading uplink channel of a cellular network, with joint cell-site processing, where unlike previous results, the error-free backhaul network has finite capacity per-cell. Namely, the cell-sites are linked to the central joint processor via lossless links with finite capacity. The cellular network is modeled by the circular Wyner model, which yields closed form expressions for the achievable rates. For this idealistic model, we present achievable rates for cell-sites that use compress-and forward scheme, combined with local decoding, and inter-cell time-sharing. These rates are then demonstrated to be rather close to the optimal unlimited backhaul joint processing rates, already for modest backhaul capacities, supporting the potential gain offered by the joint cell-site processing approach. A linear pre-processing plus encoding scheme is proposed, which significantly enhances cellular downlink performance, while putting the complexity burden on the transmitting end. The approach is based on LQ factorization of the channel transfer matrix combined with the "writing on dirty paper" approach (Caire, G. and Shamai, S., Proc. 38th Annual Allerton Conference on Communication, Control and Computing, 2000) for eliminating the effect of uncorrelated interference, which is fully known at the transmitter but unknown at the receiver. The attainable average rates with the proposed scheme approach those of optimum joint processing at the high SNR region. We study the potential benefits of base-station (BS) cooperation for downlink transmission in multicell networks. Based on a modified Wyner-type model with users clustered at the cell-edges, we analyze the dirty-paper-coding (DPC) precoder and several linear precoding schemes, including cophasing, zero-forcing (ZF), and MMSE precoders. For the nonfading scenario with random phases, we obtain analytical performance expressions for each scheme. In particular, we characterize the high signal-to-noise ratio (SNR) performance gap between the DPC and ZF precoders in large networks, which indicates a singularity problem in certain network settings. Moreover, we demonstrate that the MMSE precoder does not completely resolve the singularity problem. However, by incorporating path gain fading, we numerically show that the singularity problem can be eased by linear precoding techniques aided with multiuser selection. By extending our network model to include cell-interior users, we determine the capacity regions of the two classes of users for various cooperative strategies. In addition to an outer bound and a baseline scheme, we also consider several locally cooperative transmission approaches. The resulting capacity regions show the tradeoff between the performance improvement and the requirement for BS cooperation, signal processing complexity, and channel state information at the transmitter (CSIT). Recently, the remarkable capacity potential of multiple-input multiple-output (MIMO) wireless communication systems was unveiled. The predicted enormous capacity gain of MIMO is nonetheless significantly limited by cochannel interference (CCI) in realistic cellular environments. The previously proposed advanced receiver technique improves the system performance at the cost of increased receiver complexity, and the achieved system capacity is still significantly away from the interference-free capacity upper bound, especially in environments with strong CCI. In this paper, base station cooperative processing is explored to address the CCI mitigation problem in downlink multicell multiuser MIMO networks, and is shown to dramatically increase the capacity with strong CCI. Both information-theoretic dirty paper coding approach and several more practical joint transmission schemes are studied with pooled and practical per-base power constraints, respectively. Besides the CCI mitigation potential, other advantages of cooperative processing including the power gain, channel rank conditioning advantage, and macrodiversity protection are also addressed. The potential of our proposed joint transmission schemes is verified with both heuristic and realistic cellular MIMO settings. Cooperative transmission by base stations (BSs) can significantly improve the spectral efficiency of multiuser, multi-cell, multiple input multiple output (MIMO) systems. We show that contrary to what is often assumed in the literature, the multiuser interference in such systems is fundamentally asynchronous. Intuitively, perfect timing-advance mechanisms can at best only ensure that the desired signal components -but not also the interference components -are perfectly aligned at their intended mobile stations. We develop an accurate mathematical model for the asynchronicity, and show that it leads to a significant performance degradation of existing designs that ignore the asynchronicity of interference. Using three previously proposed linear preceding design methods for BS cooperation, we develop corresponding algorithms that are better at mitigating the impact of the asynchronicity of the interference. Furthermore, we also address timing-advance inaccuracies (jitter), which are inevitable in a practical system. We show that using jitter-statistics-aware precoders can mitigate the impact of these inaccuracies as well. The insights of this paper are critical for the practical implementation of BS cooperation in multiuser MIMO systems, a topic that is typically oversimplified in the literature. It has recently been shown that multi-cell cooperations in cellular networks, enabling distributed antenna systems and joint transmission or joint detection across cell boundaries, can significantly increase capacity, especially that of users at cell borders. Such concepts, typically implicitly assuming unlimited information exchange between base stations, can also be used to increase the network fairness. In practical implementations, however, the large amounts of received signals that need to be quantized and transmitted via an additional backhaul between the involved cells to central processing points, will be a non-negligible issue. In this paper, we thus introduce an analytical framework to observe the uplink performance of cellular networks in which joint detection is only applied to a subset of selected users, aiming at achieving best possible capacity and fairness improvements under a strongly constrained backhaul between sites. This reveals a multi-dimensional optimization problem, where we propose a simple, heuristic algorithm that strongly narrows down and serializes the problem while still yielding a significant performance improvement.