TY - GEN

T1 - Asymptotically optimal scheduling for compute-and-forward

AU - Shmuel, Ori

AU - Cohen, Asaf

AU - Gurewitz, Omer

N1 - Publisher Copyright:
© 2018 IEEE Information Theory Workshop, ITW 2018. All rights reserved.

PY - 2018/7/2

Y1 - 2018/7/2

N2 - Consider a Compute and Forward (CF) relay network with L users and a single relay. The relay tries to decode a linear function of the transmitted signals. For such a network, letting all L users transmit simultaneously, especially when L is large, causes a significant degradation in the rate in which the relay is able to decode. In fact, the rate goes to zero very fast with L. Therefore, in each transmission phase only a fixed number of users should transmit, i.e., users should be scheduled. In this work, we examine the problem of scheduling for CF and lay the foundations for identifying the optimal schedule which, to date, lacks a clear understanding. Specifically, we start with insights why when the number of users is large, good scheduling opportunities can be found. Then, we provide an asymptotically optimal, polynomial time scheduling algorithm and analyze it's performance. We conclude that scheduling under CF provides a gain in the system sum-rate, up to the optimal scaling law of O(log log L).

AB - Consider a Compute and Forward (CF) relay network with L users and a single relay. The relay tries to decode a linear function of the transmitted signals. For such a network, letting all L users transmit simultaneously, especially when L is large, causes a significant degradation in the rate in which the relay is able to decode. In fact, the rate goes to zero very fast with L. Therefore, in each transmission phase only a fixed number of users should transmit, i.e., users should be scheduled. In this work, we examine the problem of scheduling for CF and lay the foundations for identifying the optimal schedule which, to date, lacks a clear understanding. Specifically, we start with insights why when the number of users is large, good scheduling opportunities can be found. Then, we provide an asymptotically optimal, polynomial time scheduling algorithm and analyze it's performance. We conclude that scheduling under CF provides a gain in the system sum-rate, up to the optimal scaling law of O(log log L).

UR - http://www.scopus.com/inward/record.url?scp=85062081073&partnerID=8YFLogxK

U2 - 10.1109/ITW.2018.8613484

DO - 10.1109/ITW.2018.8613484

M3 - Conference contribution

AN - SCOPUS:85062081073

T3 - 2018 IEEE Information Theory Workshop, ITW 2018

BT - 2018 IEEE Information Theory Workshop, ITW 2018

PB - Institute of Electrical and Electronics Engineers

T2 - 2018 IEEE Information Theory Workshop, ITW 2018

Y2 - 25 November 2018 through 29 November 2018

ER -