We propose a multihopping decode and forward relaying protocol for two-stage Gaussian relay networks with half-duplex nodes. We analytically show that the achievable rates in suitably defined strong and weak interference regimes are close to the cut-set bound. © 2012 IEEE.

Srikrishna Bhashyam

Department of Electrical Engineering

Andrew Edwin Thangaraj

Achievable rate

Cut-set bound

DECODE-AND-FORWARD PROTOCOLS

DECODE-AND-FORWARD RELAYING

GAUSSIAN RELAY NETWORKS

HALF-DUPLEX

HALF-DUPLEX RELAY

MULTI-HOPPING

Two stage

Communication

Electronics engineering

Bandwidth

Fulltext

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

A Decode and Forward Protocol for Two-Stage Gaussian Relay Networks

IEEE Transactions on Communications

In this paper, the Gaussian many-to-one X channel (XC), which is a special case of general multiuser XC, is studied. In the Gaussian many-to-one XC, communication links exist between all transmitters and one of the receivers, along with a communication link between each transmitter and its corresponding receiver. As per the XC assumption, transmission of messages is allowed on all the links of the channel. This communication model is different from the corresponding manyto- one interference channel (IC). Transmission strategies, which involve using Gaussian codebooks and treating interference from a subset of transmitters as noise, are formulated for the above channel. Sum-rate is used as the criterion of optimality for evaluating the strategies. Initially, a 3 × 3 many-to-one XC is considered and three transmission strategies are analyzed. The first two strategies are shown to achieve sum-rate capacity under certain channel conditions. For the third strategy, a sum-rate outer bound is derived and the gap between the outer bound and the achieved rate is characterized. These results are later extended to the K × K case. Next, a region in which the many-to-one XC can be operated as a many-to-one IC without the loss of sum-rate is identified. Furthermore, in the above region, it is shown that using Gaussian codebooks and treating interference as noise achieve a rate point that is within K/2 - 1 bits from the sum-rate capacity. Subsequently, some implications of the above results to the Gaussian many-to-one IC are discussed. Transmission strategies for the many-to-one IC are formulated, and channel conditions under which the strategies achieve sum-rate capacity are obtained. A region where the sum-rate capacity can be characterized to within K/2 - 1 bits is also identified. Finally, the regions where the derived channel conditions are satisfied for each strategy are illustrated for a 3 × 3 many-to-one XC and the corresponding many-to-one IC. © 2015 IEEE.

IEEE Transactions on Information Theory

On the Gaussian many-to-one X channel

We study the Gaussian many-to-one interference network which is a special case of general interference network, where only one receiver experiences interference. We allow transmission of messages on all the links of the network. This communication model is different from the corresponding many-to-one interference channel. We formulate three transmission strategies for the above network, which involve using Gaussian codebooks and treating interference from a subset of the transmitters as noise. We use sum-rate as the criterion of optimality for evaluating the strategies. For the first two strategies, we characterize the sum-rate capacity under certain channel conditions, while for the other strategy, we derive a sum-rate outer bound and characterize the gap between the outer bound and the achievable sum-rate of the strategy. Finally, we illustrate the regions where the derived channel conditions are satisfied for each strategy. © 2014 IEEE.

2014 IEEE International Conference on Communications, ICC 2014

Optimum transmission strategies for the Gaussian many-to-one interference network

We study the Gaussian one-to-many interference network which is obtained as a special case of a general interference network, where only one transmitter generates interference in the network. We allow transmission of messages on all the links of the network. This communication model is different from the corresponding one-to-many interference channel. We formulate two transmission strategies for the above network, which involve using Gaussian codebooks and treating interference as noise at a subset of the receivers. We use sum-rate as the criterion of optimality for evaluating the strategies. For the first strategy, we characterize the sum-rate capacity under certain channel conditions, while for the second strategy, we derive a sum-rate outer bound and characterize the gap between the outer bound and the achievable sum-rate of the strategy. Next, we show that the solution approach for the second strategy has applications to the cascade Gaussian Z network, a network consisting of parallel point-to-point links, where each transmitter except the last has a communication link to the adjacent receiver. Lastly, we illustrate the regions corresponding to the derived channel conditions for each strategy. © 2014 IEEE.

IEEE Wireless Communications and Networking Conference, WCNC

Optimum transmission strategies for the Gaussian one-to-many interference network

In an M × N interference network, there are M transmitters and N receivers with each transmitter having independent messages for each of the 2N - 1 possible non-empty subsets of the receivers. We consider the 2 × 2 interference network with 6 possible messages, of which the 2 × 2 interference channel and X channel are special cases obtained by using only 2 and 4 messages respectively. Starting from an achievable rate region similar to the Han-Kobayashi region, we obtain an achievable sum rate. For the Gaussian interference network, we determine which of the 6 messages are sufficient for maximizing the sum rate within this rate region for the low, mixed, and strong interference conditions. It is observed that 2 messages are sufficient in several cases. Finally, we show that sum capacity is achieved using only 2 messages for a subset of the mixed interference conditions. © 2012 IEEE.

Journal	IEEE Transactions on Communications
ISSN	00906778
Open Access	Yes