Book contents
- Frontmatter
- Contents
- Figures
- Tables
- Preface
- 1 Introduction
- 2 Models and Preliminaries
- 3 Single-Cell Systems
- 4 Multi-Cell Systems
- 5 Power Control Principles
- 6 Case Studies
- 7 The Massive Mimo Propagation Channel
- 8 Final Notes and Future Directions
- A Circularly Symmetric Complex Gaussian Vectors
- B Useful Random Matrix Results
- C Capacity and Capacity Bounding Tools
- D Alternative Single-Cell Capacity Bounds
- E Asymptotic Sinr in Multi-Cell Systems
- F Link Budget Calculations
- G Uniformly Distributed Points in A Hexagon
- H Summary Of Abbreviations and Notation
- References
- Index
6 - Case Studies
Published online by Cambridge University Press: 03 November 2016
- Frontmatter
- Contents
- Figures
- Tables
- Preface
- 1 Introduction
- 2 Models and Preliminaries
- 3 Single-Cell Systems
- 4 Multi-Cell Systems
- 5 Power Control Principles
- 6 Case Studies
- 7 The Massive Mimo Propagation Channel
- 8 Final Notes and Future Directions
- A Circularly Symmetric Complex Gaussian Vectors
- B Useful Random Matrix Results
- C Capacity and Capacity Bounding Tools
- D Alternative Single-Cell Capacity Bounds
- E Asymptotic Sinr in Multi-Cell Systems
- F Link Budget Calculations
- G Uniformly Distributed Points in A Hexagon
- H Summary Of Abbreviations and Notation
- References
- Index
Summary
The case studies in this chapter are of two types: first, a single isolated cell for rural broadband fixed access (Section 6.1); second, multi-cell deployments for dense urban and suburban mobile access (Section 6.3). We model all important physical phenomena, including randomness of terminal locations, path loss, and shadow fading, and use the capacity expressions derived in Chapters 3–5. These expressions account for the effects of intra- and inter-cell interference, channel estimation errors, and the cost of pilot transmission. While all capacity bounds in Chapters 3 and 4 are rigorous and all algorithms in Chapter 5 provide exact solutions to precise optimization problems, in the multi-cell design examples some heuristic algorithms are needed for terminal-to-base station assignment, pilot assignment, and power control; we describe these algorithms in Section 6.2.
Tables 6.1–6.3 summarize all parameters used in the three design examples, and the resulting performance. The numbers given in Tables 6.2 and 6.3 represent 95% likely values (over the randomness associated with the large-scale fading), for the coverage probabilities specified in Table 6.1. Specifically, in the rural scenario, all 3000 homes obtain 20 Mb/s in the downlink and 10 Mb/s in the uplink, i.e., the coverage probability is 100%; Tables 6.2 and 6.3 list the numbers of antennas that are needed, with 95% probability, to offer this service. In the mobile access scenario, the coverage probability is 95% – that is, 5% of all terminals are dropped from service. The throughput numbers in Tables 6.2 and 6.3 represent the 95% likely throughput for the terminals that remain in service. For the mobile access scenarios, therefore, the overall reliability is equal to 0.95 × 0.95.
Single-Cell Deployment Example: Fixed Broadband Access in Rural Area
A single Massive MIMO base station serves 3000 homes in a rural area with data rates comparable to cable- or fiber-based access. We assume an isolated cell, for example a rural town, which is therefore free from inter-cell interference.
- Type
- Chapter
- Information
- Fundamentals of Massive MIMO , pp. 115 - 138Publisher: Cambridge University PressPrint publication year: 2016