Abstract
A gradual neural network (GNN) algorithm is presented for the jointly time-slot/code assignment problem (JTCAP) in a packet radio network in this paper. The goal of this newly defined problem is to find a simultaneous assignment of a time-slot and a code to each communication link, whereas time-slots and codes have been independently assigned in existing algorithms. A time/code division multiple access protocol is adopted for conflict-free communications, where packets are transmitted in repetition of fixed-length time-slots with specific codes. GNN seeks the time-slot/code assignment with the minimum number of time-slots subject to two constraints: 1) the number of codes must not exceed its upper limit and 2) any couple of links within conflict distance must not be assigned to the same time-slot/code pair. The restricted problem for only one code is known to be NP-complete. The performance of GNN is verified through solving 3000 instances with 100-500 nodes and 100-1000 links. The comparison with the lower bound and a greedy algorithm shows the superiority of GNN in terms of the solution quality with the comparable computation time.
| Original language | English |
|---|---|
| Pages (from-to) | 1523-1528 |
| Number of pages | 6 |
| Journal | IEEE Transactions on Neural Networks |
| Volume | 9 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 1998 |
| Externally published | Yes |
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Keywords
- Code
- Gradual neural network
- NP-complete
- Packet radio network
- Time-slot
ASJC Scopus subject areas
- Control and Systems Engineering
- Theoretical Computer Science
- Electrical and Electronic Engineering
- Artificial Intelligence
- Computational Theory and Mathematics
- Hardware and Architecture
Cite this
A gradual neural-network algorithm for jointly time-slot/code assignment problems in packet radio networks. / Funabiki, Nobuo; Kitamichi, Junji.
In: IEEE Transactions on Neural Networks, Vol. 9, No. 6, 1998, p. 1523-1528.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A gradual neural-network algorithm for jointly time-slot/code assignment problems in packet radio networks
AU - Funabiki, Nobuo
AU - Kitamichi, Junji
PY - 1998
Y1 - 1998
N2 - A gradual neural network (GNN) algorithm is presented for the jointly time-slot/code assignment problem (JTCAP) in a packet radio network in this paper. The goal of this newly defined problem is to find a simultaneous assignment of a time-slot and a code to each communication link, whereas time-slots and codes have been independently assigned in existing algorithms. A time/code division multiple access protocol is adopted for conflict-free communications, where packets are transmitted in repetition of fixed-length time-slots with specific codes. GNN seeks the time-slot/code assignment with the minimum number of time-slots subject to two constraints: 1) the number of codes must not exceed its upper limit and 2) any couple of links within conflict distance must not be assigned to the same time-slot/code pair. The restricted problem for only one code is known to be NP-complete. The performance of GNN is verified through solving 3000 instances with 100-500 nodes and 100-1000 links. The comparison with the lower bound and a greedy algorithm shows the superiority of GNN in terms of the solution quality with the comparable computation time.
AB - A gradual neural network (GNN) algorithm is presented for the jointly time-slot/code assignment problem (JTCAP) in a packet radio network in this paper. The goal of this newly defined problem is to find a simultaneous assignment of a time-slot and a code to each communication link, whereas time-slots and codes have been independently assigned in existing algorithms. A time/code division multiple access protocol is adopted for conflict-free communications, where packets are transmitted in repetition of fixed-length time-slots with specific codes. GNN seeks the time-slot/code assignment with the minimum number of time-slots subject to two constraints: 1) the number of codes must not exceed its upper limit and 2) any couple of links within conflict distance must not be assigned to the same time-slot/code pair. The restricted problem for only one code is known to be NP-complete. The performance of GNN is verified through solving 3000 instances with 100-500 nodes and 100-1000 links. The comparison with the lower bound and a greedy algorithm shows the superiority of GNN in terms of the solution quality with the comparable computation time.
KW - Code
KW - Gradual neural network
KW - NP-complete
KW - Packet radio network
KW - Time-slot
UR - http://www.scopus.com/inward/record.url?scp=0032208195&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0032208195&partnerID=8YFLogxK
U2 - 10.1109/72.728402
DO - 10.1109/72.728402
M3 - Article
C2 - 18255830
AN - SCOPUS:0032208195
VL - 9
SP - 1523
EP - 1528
JO - IEEE Transactions on Neural Networks and Learning Systems
JF - IEEE Transactions on Neural Networks and Learning Systems
SN - 2162-237X
IS - 6
ER -