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Song-Nam Hong

Publications and source records attributed to Song-Nam Hong.

40 records · Page 3Linked to original sources

Structured Lattice Codes for 2 \times 2 \times 2 MIMO Interference Channel

We consider the 2\times 2\times 2 multiple-input multipleoutput interference channel where two source-destination pairs wish to communicate with the aid of two intermediate relays. In this paper, we propose a novel lattice strategy called Aligned Precoded Compute-and-Forward (PCoF). This scheme consists of two phases: 1) Using the CoF framework based on signal alignment we transform the Gaussian network into a deterministic finite field network. 2) Using linear precoding (over finite field) we eliminate the end-to-end interference in the finite field domain. Further, we exploit the algebraic structure of lattices to enhance the performance at finite SNR, such that beyond a degree of freedom result (also achievable by other means). We can also show that Aligned PCoF outperforms time sharing in a range of reasonably moderate SNR, with increasing gain as SNR increases.

cs.IT↗

Generalized Degrees of Freedom for Network-Coded Cognitive Interference Channel

We study a two-user cognitive interference channel (CIC) where one of the transmitters (primary) has knowledge of a linear combination (over an appropriate finite field) of the two information messages. We refer to this channel model as Network-Coded CIC, since the linear combination may be the result of some linear network coding scheme implemented in the backbone wired network.In this paper, we characterize the generalized degrees of freedom (GDoF) for the Gaussian Network-Coded CIC. For achievability, we use the novel Precoded Compute-and-Forward (PCoF) and Dirty Paper Coding (DPC), based on nested lattice codes. As a consequence of the GDoF characterization, we show that knowing "mixed data" (linear combinations of the information messages) provides a {\em multiplicative} gain for the Gaussian CIC, if the power ratio of signal-to-noise (SNR) to interference-to-noise (INR) is larger than certain threshold. For example, when $\SNR=\INR$, the Network-Coded cognition yields a 100% gain over the classical Gaussian CIC.

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Reverse Compute and Forward: A Low-Complexity Architecture for Downlink Distributed Antenna Systems

We consider a distributed antenna system where $L$ antenna terminals (ATs) are connected to a Central Processor (CP) via digital error-free links of finite capacity $R_0$, and serve $L$ user terminals (UTs). This system model has been widely investigated both for the uplink and the downlink, which are instances of the general multiple-access relay and broadcast relay networks. In this work we focus on the downlink, and propose a novel downlink precoding scheme nicknamed "Reverse Quantized Compute and Forward" (RQCoF). For this scheme we obtain achievable rates and compare with the state of the art available in the literature. We also provide simulation results for a realistic network with fading and pathloss with $K > L$ UTs, and show that channel-based user selection produces large benefits and essentially removes the problem of rank deficiency in the system matrix.

cs.IT↗

Quantized Compute and Forward: A Low-Complexity Architecture for Distributed Antenna Systems

We consider a low-complexity version of the Compute and Forward scheme that involves only scaling, offset (dithering removal) and scalar quantization at the relays. The proposed scheme is suited for the uplink of a distributed antenna system where the antenna elements must be very simple and are connected to a oint processor via orthogonal perfect links of given rate R0. We consider the design of non-binary LDPC codes naturally matched to the proposed scheme. Each antenna element performs individual (decentralized) Belief Propagation decoding of its own quantized signal, and sends a linear combination of the users' information messages via the noiseless link to the joint processor, which retrieves the users' messages by Gaussian elimination. The complexity of this scheme is linear in the coding block length and polynomial in the system size (number of relays).

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