Results 1  10
of
189
Computeandforward: Harnessing interference through structured codes
 IEEE TRANS. INF. THEORY
, 2009
"... ..."
Capacity of the Gaussian Twoway Relay Channel to within 1 2 Bit
, 902
"... In this paper, a Gaussian twoway relay channel, where two source nodes exchange messages with each other through a relay, is considered. We assume that all nodes operate in fullduplex mode and there is no direct channel between the source nodes. We propose an achievable scheme composed of nested l ..."
Abstract

Cited by 96 (2 self)
 Add to MetaCart
(Show Context)
In this paper, a Gaussian twoway relay channel, where two source nodes exchange messages with each other through a relay, is considered. We assume that all nodes operate in fullduplex mode and there is no direct channel between the source nodes. We propose an achievable scheme composed of nested lattice codes for the uplink and structured binning for the downlink. We show that the scheme achieves within 1 2 bit from the cutset bound for all channel parameters and becomes asymptotically optimal as the signal to noise ratios increase. Index Terms Twoway relay channel, wireless networks, network coding, lattice codes
Optimal Beamforming for TwoWay MultiAntenna Relay Channel with Analogue Network Coding
, 2009
"... This paper studies the wireless twoway relay channel (TWRC), where two source nodes, S1 and S2, exchange information through an assisting relay node, R. It is assumed that R receives the sum signal from S1 and S2 in one timeslot, and then amplifies and forwards the received signal to both S1 and S ..."
Abstract

Cited by 90 (6 self)
 Add to MetaCart
This paper studies the wireless twoway relay channel (TWRC), where two source nodes, S1 and S2, exchange information through an assisting relay node, R. It is assumed that R receives the sum signal from S1 and S2 in one timeslot, and then amplifies and forwards the received signal to both S1 and S2 in the next timeslot. By applying the principle of analogue network coding (ANC), each of S1 and S2 cancels the socalled “selfinterference ” in the received signal from R and then decodes the desired message. Assuming that S1 and S2 are each equipped with a single antenna and R with multiantennas, this paper analyzes the capacity region of the ANCbased TWRC with linear processing (beamforming) at R. The capacity region contains all the achievable bidirectional ratepairs of S1 and S2 under the given transmit power constraints at S1, S2, and R. We present the optimal relay beamforming structure as well as an efficient algorithm to compute the optimal beamforming matrix based on convex optimization techniques. Lowcomplexity suboptimal relay beamforming schemes are also presented, and their achievable rates are compared against the capacity with the optimal scheme.
Optimized Constellations for Two–Way Wireless Relaying with Physical Network Coding
 IEEE JOURNAL OF SELECTED AREAS IN COMMUN.
, 2016
"... ..."
Capacity bounds for twoway relay channels
 in International Zurich Seminar on Communications (IZS 2008
, 2008
"... Abstract—We provide achievable rate regions for twoway relay channels (TRC). At first, for a binary TRC, we show that the subspacesharing of linear codes can achieve the capacity region. And, for a Gaussian TRC, we propose the subsetsharing of lattice codes. In some cases, the proposed lattice co ..."
Abstract

Cited by 61 (5 self)
 Add to MetaCart
(Show Context)
Abstract—We provide achievable rate regions for twoway relay channels (TRC). At first, for a binary TRC, we show that the subspacesharing of linear codes can achieve the capacity region. And, for a Gaussian TRC, we propose the subsetsharing of lattice codes. In some cases, the proposed lattice coding scheme can achieve within 1/2bit the capacity and is asymptotically optimal at high signaltonoise ratio (SNR) regimes. I.
The multiway relay channel
 in Proc. IEEE Int. Symposium on Inf. Theory (ISIT), Seoul, Korea
"... Abstract—The multiuser communication channel, in which multiple users exchange information with the help of a single relay terminal, called the multiway relay channel, is considered. In this model, multiple interfering clusters of users communicate simultaneously, where the users within the same c ..."
Abstract

Cited by 59 (3 self)
 Add to MetaCart
(Show Context)
Abstract—The multiuser communication channel, in which multiple users exchange information with the help of a single relay terminal, called the multiway relay channel, is considered. In this model, multiple interfering clusters of users communicate simultaneously, where the users within the same cluster wish to exchange messages among themselves. It is assumed that the users cannot receive each other’s signals directly, and hence the relay terminal is the enabler of communication. A relevant metric to study in this scenario is the symmetric rate achievable by all users, which we identify for amplifyandforward (AF), decodeandforward (DF) and compressandforward (CF) protocols. We also present an upper bound for comparison. The two extreme cases, namely full data exchange, in which every user wants to receive messages of all other users, and pairwise data exchange, consisting of multiple twoway relay channels, are investigated and presented in detail. I.
Channel Coding and Decoding in a Relay System Operated with PhysicalLayer Network Coding
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 2009
"... This paper investigates linkbylink channelcoded PNC (Physical layer Network Coding), in which a critical process at the relay is to transform the superimposed channelcoded packets received from the two end nodes (plus noise), Y3 = X1 + X2+W3, to the networkcoded combination of the source packet ..."
Abstract

Cited by 56 (8 self)
 Add to MetaCart
(Show Context)
This paper investigates linkbylink channelcoded PNC (Physical layer Network Coding), in which a critical process at the relay is to transform the superimposed channelcoded packets received from the two end nodes (plus noise), Y3 = X1 + X2+W3, to the networkcoded combination of the source packets, S1 ⊕ S2. This is in contrast to the traditional multipleaccess problem, in which the goal is to obtain both S1 and S2 explicitly at the relay node. Trying to obtain S1 and S2 explicitly is an overkill if we are only interested in S1⊕S2. In this paper, we refer to the transformation Y3 → S1 ⊕ S2 as the ChanneldecodingNetworkCoding process (CNC) in that it involves both channel decoding and network coding operations. This paper shows that if we adopt the Repeat Accumulate (RA) channel code at the two end nodes, then there is a compatible decoder at the relay that can perform the transformation Y3 → S1 ⊕S2 efficiently. Specifically, we redesign the belief propagation decoding algorithm of the RA code for traditional pointtopoint channel to suit the need of the PNC multipleaccess channel. Simulation results show that our new scheme outperforms the previously proposed schemes significantly in terms of BER without added complexity.
Reliable physical layer network coding
 PROCEEDINGS OF THE IEEE
, 2011
"... When two or more users in a wireless network transmit simultaneously, their electromagnetic signals are linearly superimposed on the channel. As a result, a receiver that is interested in one of these signals sees the others as unwanted interference. This property of the wireless medium is typicall ..."
Abstract

Cited by 54 (5 self)
 Add to MetaCart
(Show Context)
When two or more users in a wireless network transmit simultaneously, their electromagnetic signals are linearly superimposed on the channel. As a result, a receiver that is interested in one of these signals sees the others as unwanted interference. This property of the wireless medium is typically viewed as a hindrance to reliable communication over a network. However, using a recently developed coding strategy, interference can in fact be harnessed for network coding. In a wired network, (linear) network coding refers to each intermediate node taking its received packets, computing a linear combination over a finite field, and forwarding the outcome towards the destinations. Then, given an appropriate set of linear combinations, a destination can solve for its desired packets. For certain topologies, this strategy can attain significantly higher throughputs over routingbased strategies. Reliable physical layer network coding takes this idea one step further: using judiciously chosen linear errorcorrecting codes, intermediate nodes in a wireless network can directly recover linear combinations of the packets from the observed noisy superpositions of transmitted signals. Starting with some simple examples, this survey explores the core ideas behind this new technique and the possibilities it offers for communication over interferencelimited wireless networks.
The case for structured random codes in network capacity theorems
 in Proceedings of the IEEE Information Theory Workshop (ITW 2007), (Lake Tahoe, CA
, 2007
"... Random coding arguments are the backbone of most channel capacity achievability proofs. In this paper, we show that in their standard form, such arguments are insufficient for proving some network capacity theorems: structured coding arguments, such as random linear or lattice codes, attain higher r ..."
Abstract

Cited by 52 (10 self)
 Add to MetaCart
(Show Context)
Random coding arguments are the backbone of most channel capacity achievability proofs. In this paper, we show that in their standard form, such arguments are insufficient for proving some network capacity theorems: structured coding arguments, such as random linear or lattice codes, attain higher rates. Historically, structured codes have been studied as a stepping stone to practical constructions. However, Körner and Marton demonstrated their usefulness for capacity theorems through the derivation of the optimal rate region of a distributed functional source coding problem. Here, we use multicasting over finite field and Gaussian multipleaccess networks as canonical examples to demonstrate that even if we want to send bits over a network, structured codes succeed where simple random codes fail. Beyond network coding, we also consider distributed computation over noisy channels and a special relaytype problem. I.
Providing Secrecy With Structured Codes: Tools and Applications to TwoUser Gaussian Channels
, 2009
"... Recent results have shown that structured codes can be used to construct good channel codes, source codes and physical layer network codes for Gaussian channels. For Gaussian channels with secrecy constraints, however, efforts to date rely on random codes. In this work, we advocate that structured c ..."
Abstract

Cited by 45 (17 self)
 Add to MetaCart
(Show Context)
Recent results have shown that structured codes can be used to construct good channel codes, source codes and physical layer network codes for Gaussian channels. For Gaussian channels with secrecy constraints, however, efforts to date rely on random codes. In this work, we advocate that structured codes are useful for providing secrecy, and show how to compute the secrecy rate when structured codes are used. In particular, we solve the problem of bounding equivocation rates with one important class of structured codes, i.e., nested lattice codes. Having established this result, we next demonstrate the use of structured codes for secrecy in twouser Gaussian channels. In particular, with structured codes, we prove that a positive secure degree of freedom is achievable for a large class of fully connected Gaussian channels as long as the channel is not degraded. By way of this, for these channels, we establish that structured codes outperform Gaussian random codes at high SNR. This class of channels include the twouser multiple access wiretap channel, the twouser interference channel with confidential messages and the twouser interference wiretap channel. A notable consequence of this result is that, unlike the case with Gaussian random codes, using structured codes for both transmission and cooperative jamming, it is possible to achieve an arbitrary large secrecy rate given enough power.