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202
GarciaLunaAceves, “The capacity and energy efficiency of wireless ad hoc networks with multipacket reception
 in MobiHoc’08, 2008
"... We address the cost incurred in increasing the transport capacity of wireless ad hoc networks over what can be attained when sources and destinations communicate over multihop paths and nodes can transmit or receive at most one packet at a time. We define the energy efficiency η(n) as the bitmeters ..."
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Cited by 14 (3 self)
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We address the cost incurred in increasing the transport capacity of wireless ad hoc networks over what can be attained when sources and destinations communicate over multihop paths and nodes can transmit or receive at most one packet at a time. We define the energy efficiency η(n) as the bitmeters of information transferred in the network for each unit energy. We compute the energy efficiency of many different techniques aimed at increasing the capacity of wireless networks and show that, in order to achieve higher transport capacity, a lower energy efficiency must be attained. Using the physical model, we compute the throughput capacity of random wireless ad hoc networks in which nodes are endowed with multipacket reception (MPR) capabilities. We
Efficiency of Wireless Networks: Approximation Algorithms for the Physical Interference Model
, 2010
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Decodeandforward twoway relaying with network coding and opportunistic relay selection
 IEEE Trans. Commun
, 2010
"... All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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Cited by 12 (0 self)
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All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
Multipleinput multipleoutput twoway relaying: A spacedivision approach
 IEEE TRANS. INF. THEORY
, 2013
"... We propose a novel spacedivisionbased networkcoding scheme for multipleinput multipleoutput (MIMO) twoway relay channels (TWRCs), in which two multiantenna users exchange information via a multiantenna relay. In the proposed scheme, the overall signal space at the relay is divided into two s ..."
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Cited by 12 (8 self)
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We propose a novel spacedivisionbased networkcoding scheme for multipleinput multipleoutput (MIMO) twoway relay channels (TWRCs), in which two multiantenna users exchange information via a multiantenna relay. In the proposed scheme, the overall signal space at the relay is divided into two subspaces. In one subspace, the spatial streams of the two users have nearly orthogonal directions and are completely decoded at the relay. In the other subspace, the signal directions of the two users are nearly parallel, and linear functions of the spatial streams are computed at the relay, following the principle of physicallayer network coding. Based on the recovered messages and messagefunctions, the relay generates and forwards networkcoded messages to the two users. We show that, at high signaltonoise ratio, the proposed scheme achieves the asymptotic sumrate capacity of the MIMO TWRC within bits per userantenna, for any antenna configuration and any channel realization. We perform largesystem analysis to derive the average sumrate of the proposed scheme over Rayleighfading MIMO TWRCs. We show that the average asymptotic sumrate gap to the capacity is at most 0.053 bits per relayantenna. It is demonstrated that the proposed scheme significantly outperforms the existing schemes.
Wireless MIMO switching with zero forcing and network coding
 IEEE J. Sel. Areas Commun
, 2012
"... Abstract — A wireless relay with multiple antennas is called a multipleinputmultipleoutput (MIMO) switch if it forms a onetoone mapping from the inputs (uplinks) to the outputs (downlinks). This paper studies the case with N source stations and N destination stations (which may be the same set) ..."
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Cited by 10 (6 self)
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Abstract — A wireless relay with multiple antennas is called a multipleinputmultipleoutput (MIMO) switch if it forms a onetoone mapping from the inputs (uplinks) to the outputs (downlinks). This paper studies the case with N source stations and N destination stations (which may be the same set), so that the mapping is any permutation of the N inputs. Moreover, the switching is achieved by “precodeandforward”, i.e., the relay precodes the received vector signal by a zeroforcing matrix and transmits it, so that each destination station receives only its desired signal with enhanced noise but no interference. Assuming full channel state information is available at the switch, the design of the zeroforcing precoder for maximizing some performance metric based on the received signaltonoise ratios is investigated. The problem with two stations is completely solved in closed form in certain cases. In other cases, heuristic algorithms are proposed to optimize the precoder. These algorithms are shown to be nearoptimal. Index Terms—Beamforming, fairness, maxmin, MIMO switching, relay, zeroforcing. I.
Wireless MIMO switching: Weighted sum mean square error and sum rate optimization
 IEEE TRANS. INF. THEORY
, 2013
"... This paper addresses joint transceiver and relay design for a wireless multipleinput multipleoutput (MIMO) switching scheme that enables data exchange amongmultiple users. Here, a multiantenna relay linearly precodes the received (uplink) signals frommultiple users and forwards the signal in the ..."
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Cited by 9 (4 self)
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This paper addresses joint transceiver and relay design for a wireless multipleinput multipleoutput (MIMO) switching scheme that enables data exchange amongmultiple users. Here, a multiantenna relay linearly precodes the received (uplink) signals frommultiple users and forwards the signal in the downlink, where the purpose of precoding is to let each user receive its desired signal with interference from other users suppressed. The problem of optimizing the precoder based on various design criteria is typically nonconvex and difficult to solve. Themain contribution of this paper is a unified approach to solve the weighted summean square error (MSE) minimization and weighted sum rate maximization problems inMIMOswitching. Specifically, an iterative algorithm is proposed for jointly optimizing the relay’s precoder and the users’ receive filters to minimize the weighted sum MSE. It is also shown that the weighted sum rate maximization problem can be reformulated as an iterated weighted sumMSEminimization problem and can, therefore, be solved similarly to the case of weighted sumMSE minimization. With properly chosen initial values, the proposed iterative algorithms are asymptotically optimal in both high and lowsignaltonoiseratio regimes for MIMO switching, either with or without selfinterference cancellation (a.k.a., physicallayer network coding). Numerical results show that the optimized MIMO switching scheme based on the proposed algorithms significantly outperforms existing approaches in the literature.
Complexity of Scheduling with Analog Network Coding
, 2008
"... In this paper we analyze the complexity of scheduling wireless links in the physical interference model with analog network coding capability. We study two models with different definitions of network coding. In one model, we assume that a receiver is able to decode several signals simultaneously, p ..."
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Cited by 9 (4 self)
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In this paper we analyze the complexity of scheduling wireless links in the physical interference model with analog network coding capability. We study two models with different definitions of network coding. In one model, we assume that a receiver is able to decode several signals simultaneously, provided that these signals differ in strength significantly. In the second model, we assume that routers are able to forward the interfering signal of a pair of nodes that wish to exchange a message, and nodes are able to decode the “collided” message by subtracting their own contribution from the interfered signal. For each network coding definition, we construct an instance of the scheduling problem in the geometric SINR model, in which nodes are distributed in the Euclidean plane. We present NPcompleteness proofs for both scenarios.
Noncoherent PhysicalLayer Network Coding Using Binary CPFSK Modulation
"... Abstract—Physicallayer network coding is a highthroughput technique for communicating over the twoway relay channel, which consists of two terminals that communicate exclusively via an intermediate relay. An exchange of messages begins with both terminals transmitting binary data sequences simult ..."
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Abstract—Physicallayer network coding is a highthroughput technique for communicating over the twoway relay channel, which consists of two terminals that communicate exclusively via an intermediate relay. An exchange of messages begins with both terminals transmitting binary data sequences simultaneously to the relay. The relay determines the modulo2 sum of the sequences, which it modulates and broadcasts to the terminals. Since each terminal knows the information it transmitted, it can determine the information transmitted by the other terminal by subtracting its own information from the broadcast signal. Prior work on the topic of physicallayer network coding has assumed that the signals transmitted by the two terminals arrive at the relay with perfectly aligned phases, permitting coherent reception. In this paper, we relax the assumption of aligned phases and consider noncoherent reception of binary continuousphase frequencyshift keying signals. A derivation of the relay receiver is given for varying amounts of channel state information, and results are provided showing the error performance of the proposed system without an outer errorcorrecting code and with an outer turbo code. I.
On the Capacity Improvement of Multicast Traffic with Network Coding
, 809
"... Abstract—In this paper, we study the contribution of network coding (NC) in improving the multicast capacity of random wireless ad hoc networks when nodes are endowed with multipacket transmission (MPT) and multipacket reception (MPR) capabilities. We show that a per session throughput capacity of ..."
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Cited by 8 (3 self)
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Abstract—In this paper, we study the contribution of network coding (NC) in improving the multicast capacity of random wireless ad hoc networks when nodes are endowed with multipacket transmission (MPT) and multipacket reception (MPR) capabilities. We show that a per session throughput capacity of Θ ` nT 3 (n) ´ , where n is the total number of nodes and T(n) is the communication range, can be achieved as a tight bound when each session contains a constant number of sinks. Surprisingly, an identical order capacity can be achieved when nodes have only MPR and MPT capabilities. This result proves that NC does not contribute to the order capacity of multicast traffic in wireless ad hoc networks when MPR and MPT are used in the network. The result is in sharp contrast to the general belief (conjecture) that NC improves the order capacity of multicast. Furthermore, if the communication range is selected to guarantee ” the connectivity in “ plog the network, i.e., T(n) ≥ Θ n/n, then the combination of MPR and MPT achieves a throughput capacity of Θ
Multicast Throughput Order of Network Coding in Wireless Adhoc Networks
"... Abstract—We study the contribution of network coding (NC) in improving the multicast capacity of random wireless ad hoc networks. We consider a network with n nodes distributed uniformly in a unit square, with each node acting as a source for independent information to be sent to a multicast group c ..."
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Cited by 7 (1 self)
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Abstract—We study the contribution of network coding (NC) in improving the multicast capacity of random wireless ad hoc networks. We consider a network with n nodes distributed uniformly in a unit square, with each node acting as a source for independent information to be sent to a multicast group consisting of m randomly chosen destinations. We show that in the presence of NC, the persession „ capacity « under the protocol 1 model has a tight bound of Θ √ when m = O( mnlog(n) n log(n)) and Θ ( 1 n) when m = Ω (). Furthermore, we consider the n log(n) physical model, and “ show ” that the persession “ capacity has a 1 tight bound of Θ √mn