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ABSTRACT: Base station (BS) coordination is a key technique to handle intercell interference (ICI) in cellular networks. Nevertheless, recent work on scheduling indicates that the value of coordination is less prominent when the number of users grows large. More specifically, the loss in sum rate due to ICI in uncoordinated networks can be made arbitrarily small as the number of users goes to infinity. However, the gap in performance for a finite number of users has remained unknown so far. From this perspective we study the gains of multicell zero-forcing beamforming (ZFBF) on the downlink of a Wyner-type network. We first identify the beamforming weights and the optimal scheduling policy under a per-base power constraint. To compare ZFBF with single-cell processing (SCP) we focus on the extra number of users that is needed per cell to compensate for ICI. Specifically, we find the number of users n <sub>1</sub> with ZFBF and n <sub>2</sub> with SCP that gives the same mean postscheduling signal-to-interference-plus-noise ratio (SINR) as an interference free network with n users. The results show that the ratio [( n <sub>2</sub>)/( n <sub>1</sub>)] grows logarithmically with n . Finally, we demonstrate that the difference in sum-rate between SCP and multicell ZFBF goes to zero as O ([(lnln n )/(ln n )]). As a consequence of the slow convergence there is a significant gain with multicell ZFBF for all practical numbers of users.
IEEE Transactions on Signal Processing 02/2012; · 2.63 Impact Factor
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ABSTRACT: In this paper, we assess the random coding error exponents (EEs) corresponding to decode-and-forward (DF), compress-and-forward (CF) and quantize-and-forward (QF) relaying strategies for a parallel relay network (PRN), consisting of two sources, two relay stations (RSs) and single destination where the RSs access to the destination via orthogonal, error-free, limited-capacity backhaul links. Among these relaying strategies, the DF and QF studied in this paper differ from their well-known conventional versions in certain aspects. In the DF relaying, each RS applies maximum-likelihood (ML) detection and sends the message corresponding to the detected signal along with a reliability information to the destination which finalize the decision on the transmitted message. In QF relaying, as opposed to the Gaussian codebook and vector quantization (VQ) theoretical model used for deriving bounds, we consider a simple and practical relaying strategy consisting of finite-alphabet constellations (i.e., M-QAM) at the sources and symbol-by-symbol uniform scalar quantizers (uSQs) at the RSs. We also show, through numerical analysis, that the proposed QF relaying can provide better EEs than the others when the modulation constellation sizes selected by the sources match to the network conditions, i.e., operating signal-to-noise ratio (SNR), and the backhaul capacity is sufficient. This behavior is due to the structure inherent in the considered modulation alphabets, which Gaussian signaling lacks.
Communications (ICC), 2011 IEEE International Conference on; 07/2011
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ABSTRACT: A multihop relaying system is analyzed where data sent by a multi-antenna source is relayed by successive multi-antenna relays until it reaches a multi-antenna destination. Assuming correlated fading at each hop, each relay receives a faded version of the signal from the previous level, performs linear precoding and retransmits it to the next level. Using free probability theory and assuming that the noise power at relays- but not at destination- is negligible, the closed-form expression of the asymptotic instantaneous end-to-end mutual information is derived as the number of antennas at all levels grows large. The so-obtained deterministic expression is independent from the channel realizations while depending only on channel statistics. This expression is also shown to be equal to the asymptotic average end-to-end mutual information. The singular vectors of the optimal precoding matrices, maximizing the average mutual information with finite number of antennas at all levels, are also obtained. It turns out that these vectors are aligned to the eigenvectors of the channel correlation matrices. Thus, they can be determined using only the channel statistics. As the structure of the singular vectors of the optimal precoders is independent from the system size, it is also optimal in the asymptotic regime.
IEEE Transactions on Information Theory 05/2011; · 3.01 Impact Factor
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ABSTRACT: We analyze the sum rate performance in multicell single-hop networks where access points are allowed to cooperate in terms of a joint resource allocation. The resource allocation policies considered here combine power control and user scheduling. Although promising from a conceptual point of view, the optimization of the sum of per-link rates hinges on tough issues such as computational complexity and the requirement for heavy receiver-to-transmitter and cell-to-cell channel information feedback. In this paper, however, we show that simple distributed algorithms can scale optimally in terms of rates, when the number of users per cell U is allowed to grow large. We use extreme value theory to provide scaling laws for upper and lower bounds for the network sum-rate (sum of single user rates over all cells), corresponding to zero-interference and worst-case interference scenarios. We show that the scaling is either dominated by path loss statistics or by small-scale fading, depending on the regime and user location scenario. A surprising result is that the well known log log U rate behavior exhibited in i.i.d. fading channels with maximum rate schedulers is transformed into a log U behavior when path loss is accounted for. Additionally, by showing that upper and lower rate bounds behave in fact identically, asymptotically, our results suggest, remarkably, that the impact of multicell interference on the rate (in terms of scaling) actually vanishes asymptotically, when appropriate resource allocation policies are used.
IEEE Transactions on Information Theory 02/2011; · 3.01 Impact Factor
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ABSTRACT: The one tutorial paper and eight contributed papers in this special issue focus on cooperative communications in MIMO cellular networks.
IEEE Journal on Selected Areas in Communications 01/2011; · 3.41 Impact Factor
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ABSTRACT: This paper presents an overview of the theory and currently known techniques for multi-cell MIMO (multiple input multiple output) cooperation in wireless networks. In dense networks where interference emerges as the key capacity-limiting factor, multi-cell cooperation can dramatically improve the system performance. Remarkably, such techniques literally exploit inter-cell interference by allowing the user data to be jointly processed by several interfering base stations, thus mimicking the benefits of a large virtual MIMO array. Multi-cell MIMO cooperation concepts are examined from different perspectives, including an examination of the fundamental information-theoretic limits, a review of the coding and signal processing algorithmic developments, and, going beyond that, consideration of very practical issues related to scalability and system-level integration. A few promising and quite fundamental research avenues are also suggested.
IEEE Journal on Selected Areas in Communications 01/2011; · 3.41 Impact Factor
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ABSTRACT: This paper considers the multiple-input-single-output interference channel (MISO-IC) in which transmitters and receivers share the same time and frequency resources. We consider receivers with interference decoding capability (IDC) so that the interference signal can be decoded and subtracted from the received signal. On the MISO-IC with single user decoding, transmit beamforming vectors are designed to mitigate interference at the receivers. With IDC, receivers can potentially decode interference which yields a higher data rate. Yet, decoding interference pose a rate constraint on the interferer and in turn on the sum rate of the system. This brings some interesting questions: when should the Txs mitigate interference and when should Txs amplify interference? Under what situations should Txs change from mitigating interference to amplifying interference? We answer these questions in this paper.
Signals, Systems and Computers (ASILOMAR), 2010 Conference Record of the Forty Fourth Asilomar Conference on; 12/2010
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ABSTRACT: In this work we present low-complexity coded-modulation strategies for distributed relaying in 4G wireless networks. The primary goal of these strategies is to improve coverage on the uplink while retaining high spectral efficiency through multiuser spatial-multiplexing using two or more relays between the users and the base station. We contrast layer 2 techniques based on full decoding at relay stations and simple compression-based (quantization) techniques with QAM alphabets. Mutual-information and error-exponent analysis clearly show the benefits of distributed quantization both in the high and medium spectral efficiency regions. We further present these results in the context of evolving LTE-Advanced standardization activities, primarily by suggesting adaptations to standardized coding and retransmission mechanisms for a multiple-relay system.
Signals, Systems and Computers (ASILOMAR), 2010 Conference Record of the Forty Fourth Asilomar Conference on; 12/2010
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ABSTRACT: Utilizing the real-valued parametrization of each transmitter's efficient beamforming vectors, we propose a decentralized resource allocation scheme in the multiple-input single-output interference channel. The scheme is motivated by bargaining concepts in game theory. The aim of these concepts is to improve the joint payoff of the users from the Nash equilibrium outcome. In each bargaining-step, each user proposes a strategy. A user accepts any proposal if it increases his payoff. Otherwise, new proposals are made. When all proposals are accepted, a new bargaining-stage begins. We prove the scheme's convergence and demonstrate its performance by simulations. In comparison to previous approaches, our bargaining outcome is arbitrarily close to the Pareto boundary of the achievable single-user rate region. We further discuss the control overhead and complexity of this scheme.
Signals, Systems and Computers (ASILOMAR), 2010 Conference Record of the Forty Fourth Asilomar Conference on; 12/2010
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ABSTRACT: In this paper, we assess the random coding error exponents (EEs) corresponding to decode-and-forward (DF), compress-and-forward (CF) and quantize-and-forward (QF) relaying strategies for a parallel relay network (PRN), consisting of a single source and two relays. Moreover, through numerical analysis we show that the EEs achieved by using QF relaying along with non-Gaussian signaling (coded modulation, M-QAM) at the source and symbol-by-symbol uniform scalar quantizers (uSQs) at the relays is better than that achieved by DF and CF relaying strategies when the system is in the low signal-to-noise ratio (SNR) regime and the backhaul capacity is sufficient. This behavior is due to the structure of coded modulation, as opposed to Gaussian signaling, which leads to better EEs for simple relaying strategies compared to its more complex counterparts.
Personal Indoor and Mobile Radio Communications (PIMRC), 2010 IEEE 21st International Symposium on; 10/2010
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ABSTRACT: 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.
IEEE Transactions on Wireless Communications 09/2010; · 2.59 Impact Factor
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ABSTRACT: 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.
IEEE Transactions on Signal Processing 09/2010; · 2.63 Impact Factor
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ABSTRACT: We investigate the performance of an uncoordinated 2 link MIMO interference channel as a function of the number of antennas and the average channel gains. The channel coefficients are random and uncorrelated, all links undergo Rayleigh fading, and the transmitters have no channel state information. The analysis is done in terms of ergodic capacity and outage probability. For non-asymptotic networks (i.e., when the number of transmit and receive antennas is finite and small), we derive upper and lower bounds to both our performance metrics. Moreover, the particular case of a MISO channel is considered, where exact expressions for the ergodic capacity, distribution of the capacity, and outage probability are derived. It is concluded theoretically, and somewhat surprisingly, that using all transmit antennas is not always optimal. That is, depending on the average channel gains and the requested communication rate, a transmitter should apply its antennas in different ways in order to minimize the outage probability.
Signal Processing Advances in Wireless Communications (SPAWC), 2010 IEEE Eleventh International Workshop on; 07/2010
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E.A. Jorswieck,
L. Badia,
T. Fahldieck, D. Gesbert,
S. Gustafsson,
M. Haardt,
Ka-Ming Ho,
E. Karipidis,
A. Kortke,
E.G. Larsson,
H. Mark,
M. Nawrocki,
R. Piesiewicz,
F. Römer,
M. Schubert,
J. Sykora,
P. Trommelen,
B. van den Ende,
M. Zorzi
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ABSTRACT: Physical resource sharing between wireless operators and service providers is necessary in order to support efficient, competitive, and innovative wireless communication markets. By sharing resources, such as spectrum or infrastructure, which are usually exclusively allocated interference is created on the physical layer. Therefore, the economic gains, regulatory overhead, and engineering efforts need to be addressed by a consolidated cross-layer approach. This paper describes briefly the approach taken by the EU FP7 project SAPHYRE.
Future Network and Mobile Summit, 2010; 07/2010
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ABSTRACT: This paper considers the so-called Multiple-Input Multiple-Output interference channel (MIMO-IC) which has relevance in applications such as multi-cell coordination in cellular networks as well as spectrum sharing in cognitive radio networks among others. We address the design of preceding (i.e. beamforming) vectors at each sender with the aim of striking a compromise between beamforming gain at the intended receiver (Egoism) and the mitigation of interference created towards other receivers (Altruism). Combining egoistic and altruistic beamforming has been shown previously to be instrumental to optimizing the rates in a Multiple-Input-SingleOutput (MISO) interference channel (i.e. where receivers have no interference canceling capability). Here we explore these game-theoretic concepts in the more general context of MIMO channels and use the framework of Bayesian games which allows us to derive (semi-)distributed precoding techniques. We draw parallels with important existing work on the MIMO-IC, including rate-optimizing and interference-alignment precoding techniques, and show how such techniques may be re-interpreted through a common prism based on balancing egoistic and altruistic beamforming. Our analysis and simulations attest the improvements in terms of complexity and performance.
Communications (ICC), 2010 IEEE International Conference on; 06/2010
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ABSTRACT: 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.
Communications (ICC), 2010 IEEE International Conference on; 06/2010
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ABSTRACT: This paper considers the so-called Multiple-Input-Multiple-Output interference channel (MIMO-IC). We address the design of precoding (i.e. beamforming) vectors and power control at each data stream with the aim of striking a compromise between beamforming gain at the intended receiver (Egoism) and the mitigation of interference created towards other receivers (Altruism). Combining egoistic and altruistic beamforming has been shown previously to be instrumental to optimizing the rates in a Multiple-Input-Single-Output (MISO) interference channel and MIMO-IC. Here we extend these concepts to multi-stream scenarios and further improve the rate performance by allowing power control which is not addressed in previous interference alignment related works. The key idea behind power control in interference coordination schemes is that it can help restore feasibility conditions in the high SNR regime, thus avoiding a saturation of the sum rate. Our analysis and simulations attest improvement in terms of complexity and performance.
Wireless Conference (EW), 2010 European; 05/2010
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ABSTRACT: 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.
Information Theory and Applications Workshop (ITA), 2010; 03/2010
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ABSTRACT: 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. 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.
Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE; 01/2010
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ABSTRACT: The communication between a multiple-antenna transmitter and multiple receivers (users) with either a single or multiple-antenna each can be significantly enhanced by providing the channel state information at the transmitter (CSIT) of the users, as this allows for scheduling, beamforming and multiuser multiplexing gains. The traditional view on how to enable CSIT has been as follows so far: In time-division duplexed (TDD) systems, uplink (UL) and downlink (DL) channel reciprocity allows for the use of a training sequence in any given uplink slot, which is exploited to obtain an uplink channel estimate. This estimate is in turn recycled in the next downlink slot. In frequency-division duplexed (FDD) systems, which lack the UL and DL reciprocity, the CSIT is provided via the use of a dedicated feedback link of limited capacity between the receivers and the transmitter. In this paper, we focus on TDD systems and show that the traditional TDD CSIT acquisition fails to fully exploit the channel reciprocity in its true sense. In fact, we show that the system can benefit from a combined CSIT acquisition strategy mixing the use of limited feedback and that of a training sequence. We demonstrate the potential of our approach in terms of improved CSIT quality under a global training and feedback resource constraint.
Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE; 01/2010
