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Journal Article•DOI•

Dirty Paper Coding for Gaussian Cognitive Z-Interference Channel: Performance Results

Zouhair Al-qudah1, Dinesh Rajan2•
Al-Hussein Bin Talal University1, Southern Methodist University2
07 Nov 2013-IEEE Transactions on Wireless Communications (IEEE)-Vol. 12, Iss: 12, pp 6086-6095
TL;DR: Numerical results show that causal knowledge of the interference provides more than 3 dB improvement in performance in certain scenarios over a scheme that does not use interference cancellation.
Abstract: In this paper, we present a practical application of dirty paper coding (DPC) for the Gaussian cognitive Z-interference channel. A two stage transmission scheme is proposed in which the cognitive transmitter first obtains the interference signal from the primary transmitter and then uses DPC to improve the performance of the cognitive link. Numerical results show that causal knowledge of the interference provides more than 3 dB improvement in performance in certain scenarios over a scheme that does not use interference cancellation. Results are also shown when the cognitive transmitter operates in both half-duplex and full-duplex modes.
Citations
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Journal Article•DOI•
Multiple access relay channel: Achievable rates over orthogonal channels

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Wael H. Al-Sawalmeh1, Zouhair Al-qudah1, Khalid A. Darabkh2•
Al-Hussein Bin Talal University1, University of Jordan2
01 Sep 2019-Aeu-international Journal of Electronics and Communications
TL;DR: Numerical results show that the derived achievable rate region contains the available rate region in the literature, and the sum rate has a concave relation with the number of channel uses in the listening phase.
Abstract: In this paper, we consider the multiple access relay channel (MARC) in which two users want to communicate with a destination in the presence of a common intermediate node, the relay. This paper considers the case in which the relay can partially listen to both the users until it can estimate their signals. Specifically, a two-phase transmission scheme, (i) listening phase, and (ii) forwarding phase, is designed toward deriving the achievable rate region. In particular, the achievable rate region is basically derived in the cases of additive Gaussian channel and Rayleigh fading channel. Our numerical results show that (i) the derived achievable rate region contains the available rate region in the literature, and (ii) the sum rate has a concave relation with the number of channel uses in the listening phase.

6 citations

Journal Article•DOI•
Orthogonal space-time block coding over dirty paper channel

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Zouhair Al-qudah1•
Al-Hussein Bin Talal University1
01 Jun 2015-Physical Communication
TL;DR: It is analytically prove that the outage capacity of the multiple input multiple output (MIMO) which is affected by interference, that is non-causally available as well as the channel state information (CSI) for all users at the transmitter, has the free interference outage capacity.

2 citations

Cites background from "Dirty Paper Coding for Gaussian Cog..."

  • ...For instance, consider a cognitive ZIC [12,11] in which one of the two transmitters is cognitive....

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  • ...These capacity limits have been extended to MIMO systems such as the broadcast channel [5, 8–10] and the cognitive Z-interference channel (ZIC) [11]....

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Journal Article•
On Optimal Power Allocation for Gaussian Broadcast Channel

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Zouhair Al-qudah, Mohammad Al Bataineh, Wael Abu Shehab
01 Jan 2016-Innovative Systems Design and Engineering
TL;DR: The optimal power allocation for Gaussian two users broadcast channel is derived from two optimization schemes that maximizes the sum rate capacity and the optimality of the derived schemes is verified.
Abstract: We derive the optimal power allocation for Gaussian two users broadcast channel. To find the optimal power allocation between the two users, two optimization schemes are considered. In each optimization scheme, an analytical expression for the optimal power allocation between the two users is derived. The first optimization criterion finds the optimal power allocation between the two users such that they have equal rates. Then, the optimal power allocation that maximizes the sum rate capacity is studied. In addition, numerical examples are provided to verify the optimality of the derived schemes. Keywords: Gaussian Broadcast Channel, Capacity Region, Optimization.

Cites background or methods from "Dirty Paper Coding for Gaussian Cog..."

  • ...Practically, it was indicated in [Al-qudah & Rajan,2013] that the error of estimating the common signal 2X at the first destination can dominate the error rate at this destination....

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  • ...Practically, the authors in [Al-qudah & Rajan,2013] reported that the error of estimating the common signal at the first destination can dominate the error rate at this destination....

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  • ...In order to avoid this estimation error, the transmitter can employ dirty paper coding [Al-qudah & Rajan,2013, Mazzotti & Chiani, 2006] to completely remove the effect of the common message at the first destination....

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References
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Journal Article•DOI•
Writing on dirty paper (Corresp.)

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Max Costa1•
Stanford University1
01 May 1983-IEEE Transactions on Information Theory
TL;DR: It is shown that the optimal transmitter adapts its signal to the state S rather than attempting to cancel it, which is also the capacity of a standard Gaussian channel with signal-to-noise power ratio P/N.
Abstract: A channel with output Y = X + S + Z is examined, The state S \sim N(0, QI) and the noise Z \sim N(0, NI) are multivariate Gaussian random variables ( I is the identity matrix.). The input X \in R^{n} satisfies the power constraint (l/n) \sum_{i=1}^{n}X_{i}^{2} \leq P . If S is unknown to both transmitter and receiver then the capacity is \frac{1}{2} \ln (1 + P/( N + Q)) nats per channel use. However, if the state S is known to the encoder, the capacity is shown to be C^{\ast} =\frac{1}{2} \ln (1 + P/N) , independent of Q . This is also the capacity of a standard Gaussian channel with signal-to-noise power ratio P/N . Therefore, the state S does not affect the capacity of the channel, even though S is unknown to the receiver. It is shown that the optimal transmitter adapts its signal to the state S rather than attempting to cancel it.

4,130 citations

"Dirty Paper Coding for Gaussian Cog..." refers background or methods in this paper

  • ...Therefore, the auxiliary random variable which was proposed by Costa [3] q = x+βs has to be modified to consider these channel gains....

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  • ...Subsequently, in his path breaking work, Costa [3] applied the previous capacity formula to the additive Gaussian noise channel to prove that an interference free Manuscript received November 26, 2012; revised May 24 and September 12, 2013; accepted September 13, 2013....

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  • ...In his work, Costa made two main assumptions to achieve the channel capacity, the interference is available non-causally at the transmitter only and the random variable U is designed to be U = X + βS where β is the power inflation factor....

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  • ...Subsequently, in his path breaking work, Costa [3] applied the previous capacity formula to the additive Gaussian noise channel to prove that an interference free...

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Journal Article•DOI•
On the achievable throughput of a multiantenna Gaussian broadcast channel

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Giuseppe Caire1, Shlomo Shamai2•
Institut Eurécom1, Technion – Israel Institute of Technology2
01 Jul 2003-IEEE Transactions on Information Theory
TL;DR: Under certain mild conditions, this scheme is found to be throughput-wise asymptotically optimal for both high and low signal-to-noise ratio (SNR), and some numerical results are provided for the ergodic throughput of the simplified zero-forcing scheme in independent Rayleigh fading.
Abstract: A Gaussian broadcast channel (GBC) with r single-antenna receivers and t antennas at the transmitter is considered. Both transmitter and receivers have perfect knowledge of the channel. Despite its apparent simplicity, this model is, in general, a nondegraded broadcast channel (BC), for which the capacity region is not fully known. For the two-user case, we find a special case of Marton's (1979) region that achieves optimal sum-rate (throughput). In brief, the transmitter decomposes the channel into two interference channels, where interference is caused by the other user signal. Users are successively encoded, such that encoding of the second user is based on the noncausal knowledge of the interference caused by the first user. The crosstalk parameters are optimized such that the overall throughput is maximum and, surprisingly, this is shown to be optimal over all possible strategies (not only with respect to Marton's achievable region). For the case of r>2 users, we find a somewhat simpler choice of Marton's region based on ordering and successively encoding the users. For each user i in the given ordering, the interference caused by users j>i is eliminated by zero forcing at the transmitter, while interference caused by users j

2,616 citations

"Dirty Paper Coding for Gaussian Cog..." refers background in this paper

  • ...Compared to DPC, ZF-DPC is a lower complexity but suboptimal interference cancellation technique [7], [8]....

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  • ...In addition to this DPC scheme, several other alternatives have also emerged to cancel the effect of the interference including, zero-forcing [4], [5], and zero forcing dirty paper coding (ZF-DPC)[6]....

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On the achievable throughput of a multiantenna Gaussian broadcast channels

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G. Caire
01 Jan 2004

2,180 citations

Coding for channel with random parameters

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Si Gel'fand, M. S. Pinsker
01 Jan 1980

957 citations

Journal Article•DOI•
Achieving 1/2 log (1+SNR) on the AWGN channel with lattice encoding and decoding

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Uri Erez1, Ram Zamir1•
Tel Aviv University1
01 Oct 2004-IEEE Transactions on Information Theory
TL;DR: In this article, a lattice code with lattice decoding was proposed to achieve the additive white Gaussian noise (AWGN) channel capacity, whose effective noise is reduced by a factor of /spl radic/(1+SNR/SNR) for any desired nesting ratio.
Abstract: We address an open question, regarding whether a lattice code with lattice decoding (as opposed to maximum-likelihood (ML) decoding) can achieve the additive white Gaussian noise (AWGN) channel capacity We first demonstrate how minimum mean-square error (MMSE) scaling along with dithering (lattice randomization) techniques can transform the power-constrained AWGN channel into a modulo-lattice additive noise channel, whose effective noise is reduced by a factor of /spl radic/(1+SNR/SNR) For the resulting channel, a uniform input maximizes mutual information, which in the limit of large lattice dimension becomes 1/2 log (1+SNR), ie, the full capacity of the original power constrained AWGN channel We then show that capacity may also be achieved using nested lattice codes, the coarse lattice serving for shaping via the modulo-lattice transformation, the fine lattice for channel coding We show that such pairs exist for any desired nesting ratio, ie, for any signal-to-noise ratio (SNR) Furthermore, for the modulo-lattice additive noise channel lattice decoding is optimal Finally, we show that the error exponent of the proposed scheme is lower bounded by the Poltyrev exponent

839 citations

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