1,478 research outputs found
Multi-functional MIMO communication in multi-hop cellular systems
[EN] In the context of multi-hop cellular communications, user equipment devices (UEs) with relaying capabilities provide a virtual infrastructure that can enhance the cell spectral efficiency. UE relays, which are generally transparent to the destination user and lack channel state information, mainly operate in an open-loop mode. Most open-loop transmission techniques for relaying are based on orthogonal space-time block coding (OSTBC), which offers a good trade-off between performance and complexity. In this paper, we consider the concept of multi-functional multiple-input multiple-output (MIMO) transmission, which combines OSTBC with beamforming techniques. This concept is applied to networks with multiple relays, which can offer a high number of antennas to implement multi-functional MIMO techniques. The proposed schemes are shown to reduce the bit error rate of the destination user with respect to a direct transmission from the base station (BS). Furthermore, the multi-functional setup exhibits better performance than conventional OSTBC at high transmission rates.This work was performed in the framework of the FP7 project ICT-317669 METIS, which is partly funded by the European Union. The authors would like to acknowledge the contributions of their colleagues in METIS, although the views expressed are those of the authors and do not necessarily represent the project.Roger Varea, S.; Calabuig Soler, D.; Monserrat Del RĂo, JF.; Cardona Marcet, N. (2014). Multi-functional MIMO communication in multi-hop cellular systems. EURASIP Journal on Advances in Signal Processing. 2014(165):1-9. https://doi.org/10.1186/1687-6180-2014-165S192014165Timus B, Fallgren M (Eds): In D1.1: Scenarios, requirements and KPIs for 5G mobile and wireless system. Project deliverable, ICT-317669-METIS. 2013.Zheng K, Fan B, Ma Z, Liu G, Shen X, Wang W: Multihop cellular networks toward LTE-advanced. IEEE Veh. Tech. Mag 2009, 4(3):40-47.Gozalvez J, Coll-Perales B: Experimental evaluation of multihop cellular networks using mobile relays. IEEE Commun. Mag 2013, 51(7):122-129.Zhou B, Hu H, Huang S-Q, Chen H-H: Intracluster device-to-device relay algorithm with optimal resource utilization. IEEE Trans. Veh. Tech 2013, 62(5):2315-2326.Vanganuru K, Ferrante S, Sternberg G: System capacity and coverage of a cellular network with D2D mobile relays,. In Military Communications Conference,. Orlando (FL), USA; 2012:1-6. doi:10.1109/MILCOM.2012.6415659Bölcksei H, Nabar RU, Oyman O, Paulraj AJ: Capacity scaling laws in MIMO relay networks. IEEE Trans. Wireless Comm 2006, 5(6):1433-1444.Tarokh V, Jafarkhani H, Calderbank AR: Space-time block codes from orthogonal designs. IEEE Trans. Information Theory 1999, 45(5):1456-1467. 10.1109/18.771146Wang H, Xia XG: Upper bounds of rates of complex orthogonal space-time block codes. IEEE Trans. Information Theory 2003, 49(10):2788-2796. 10.1109/TIT.2003.817830Jafarkani H: A quasi-orthogonal space–time block code. IEEE Trans. Commun 2001, 49(1):1-4. 10.1109/26.898239Nguyen XH, Choi J: Joint design of groupwise STBC and SIC based receiver. IEEE Comm. Lett 2008, 12(2):115-117.El-Hajjar M, Alamri O, Wang J, Zummo S, Hanzo L: Layered steered space-time codes using multi-dimensional sphere packing modulation. IEEE Trans. Wireless Comm 2009, 8(7):3335-3340.Laneman JN, Wornell GW: Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks. IEEE Trans. Information Theory 2003, 49(10):2415-2425. 10.1109/TIT.2003.817829Barbarossa S, Pescosolido L, Ludovici D, Barbetta L, Scutari G: Cooperative wireless networks based on distributed space-time coding,. In International Workshop on Wireless Ad-Hoc Networks,. Oulu, Finland; 2004.Jing Y, Jafarkhani H: Using orthogonal and quasi-orthogonal designs in wireless relay networks. IEEE Trans. Information Theory 2007, 53(11):4106-4118.Hayes M, Kassim SK, Chambers JA, Macleod MD: Exploitation of quasi-orthogonal space time block codes in virtual antenna arrays: Part I - theoretical capacity and throughput gains,. In IEEE Vehicular Technology Conference, VTC Spring 2008,. Singapore; 2008:349-352. doi:10.1109/VETECS.2008.84Zou Y, Yao Y-D, Zheng B: Opportunistic distributed space-time coding for decode-and-forward cooperation systems. IEEE Trans. Signal Process, 60(4):2012.Kim J, Yang JR, Kim DI: Optimal relaying strategy for UE relays,. In Asia-Pacific Conference on Communications (APCC),. Sabah, Malaysia; 2011:192-196. doi:10.1109/APCC.2011.6152803Fan Y, Thompson J: MIMO configurations for relay channels: theory and practice. IEEE Trans. Wireless Commun 2007, 6(5):1774-1786.Schulz B: LTE Transmission Modes and Beamforming. Rohde and Schwarz White Paper 2011.Forutanpour B, Schevciw AGP, Visser E, Momeyer B: Variable beamforming with a mobile platform. US Patent 20120182429 2012
Cross-Layer Optimization of Fast Video Delivery in Cache-Enabled Relaying Networks
This paper investigates the cross-layer optimization of fast video delivery
and caching for minimization of the overall video delivery time in a two-hop
relaying network. The half-duplex relay nodes are equipped with both a cache
and a buffer which facilitate joint scheduling of fetching and delivery to
exploit the channel diversity for improving the overall delivery performance.
The fast delivery control is formulated as a two-stage functional non-convex
optimization problem. By exploiting the underlying convex and quasi-convex
structures, the problem can be solved exactly and efficiently by the developed
algorithm. Simulation results show that significant caching and buffering gains
can be achieved with the proposed framework, which translates into a reduction
of the overall video delivery time. Besides, a trade-off between caching and
buffering gains is unveiled.Comment: 7 pages, 4 figures; accepted for presentation at IEEE Globecom, San
Diego, CA, Dec. 201
Iterative Deterministic Equivalents for the Performance Analysis of Communication Systems
In this article, we introduce iterative deterministic equivalents as a novel
technique for the performance analysis of communication systems whose channels
are modeled by complex combinations of independent random matrices. This
technique extends the deterministic equivalent approach for the study of
functionals of large random matrices to a broader class of random matrix models
which naturally arise as channel models in wireless communications. We present
two specific applications: First, we consider a multi-hop amplify-and-forward
(AF) MIMO relay channel with noise at each stage and derive deterministic
approximations of the mutual information after the Kth hop. Second, we study a
MIMO multiple access channel (MAC) where the channel between each transmitter
and the receiver is represented by the double-scattering channel model. We
provide deterministic approximations of the mutual information, the
signal-to-interference-plus-noise ratio (SINR) and sum-rate with
minimum-mean-square-error (MMSE) detection and derive the asymptotically
optimal precoding matrices. In both scenarios, the approximations can be
computed by simple and provably converging fixed-point algorithms and are shown
to be almost surely tight in the limit when the number of antennas at each node
grows infinitely large. Simulations suggest that the approximations are
accurate for realistic system dimensions. The technique of iterative
deterministic equivalents can be easily extended to other channel models of
interest and is, therefore, also a new contribution to the field of random
matrix theory.Comment: submitted to the IEEE Transactions on Information Theory, 43 pages, 4
figure
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Capacity and Power Scaling Laws for Finite Antenna MIMO Amplify-and-Forward Relay Networks
In this paper, we present a novel framework that can be used to study the
capacity and power scaling properties of linear multiple-input multiple-output
(MIMO) antenna amplify-and-forward (AF) relay networks. In
particular, we model these networks as random dynamical systems (RDS) and
calculate their Lyapunov exponents. Our analysis can be applied to systems
with any per-hop channel fading distribution, although in this contribution we
focus on Rayleigh fading. Our main results are twofold: 1) the total transmit
power at the th node will follow a deterministic trajectory through the
network governed by the network's maximum Lyapunov exponent, 2) the capacity of
the th eigenchannel at the th node will follow a deterministic trajectory
through the network governed by the network's th Lyapunov exponent. Before
concluding, we concentrate on some applications of our results. In particular,
we show how the Lyapunov exponents are intimately related to the rate at which
the eigenchannel capacities diverge from each other, and how this relates to
the amplification strategy and number of antennas at each relay. We also use
them to determine the extra cost in power associated with each extra
multiplexed data stream.Comment: 16 pages, 9 figures. Accepted for publication in IEEE Transactions on
Information Theor
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