Abstract
Densifying the network and deploying more antennas at each access point are two principal ways to boost the capacity of wireless networks. However, due to the complicated distributions of random signal and interference channel gains, largely induced by various space-time processing techniques, it is highly challenging to quantitatively characterize the performance of dense multi-antenna networks. In this paper, using tools from stochastic geometry, a tractable framework is proposed for the analytical evaluation of such networks. The major result is an innovative representation of the coverage probability, as an induced ℓ1-norm of a Toeplitz matrix. This compact representation incorporates lots of existing analytical results on single-and multi-antenna networks as special cases, and its evaluation is almost as simple as the single-antenna case with Rayleigh fading. To illustrate its effectiveness, we apply the proposed framework to investigate two kinds of prevalent dense wireless networks, i.e., physical layer security aware networks and millimeter-wave networks. In both examples, in addition to tractable analytical results of relevant performance metrics, insightful design guidelines are also analytically obtained.
| Original language | English |
|---|---|
| Title of host publication | 2017 IEEE International Conference on Communications, ICC 2017 |
| Publisher | IEEE |
| ISBN (Print) | 9781467389990 |
| DOIs | |
| Publication status | Published - 28 Jul 2017 |
| Externally published | Yes |
| Event | 2017 IEEE International Conference on Communications, ICC 2017 - Paris, France Duration: 21 May 2017 → 25 May 2017 |
Publication series
| Name | IEEE International Conference on Communications |
|---|---|
| ISSN (Print) | 1550-3607 |
Conference
| Conference | 2017 IEEE International Conference on Communications, ICC 2017 |
|---|---|
| Place | France |
| City | Paris |
| Period | 21/05/17 → 25/05/17 |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Funding
This work was supported by the Hong Kong Research Grants Council under Grant No. 16210216.
RGC Funding Information
- RGC-funded
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