Price-Based Resource Allocation in Massive MIMO H-CRANs with Limited Fronthaul Capacity

Wanming Hao, Osamu Muta, Haris Gacanin

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)


In this paper, we investigate the bandwidth and power allocation problem in remote radio head cluster (RRHC)-based millimeter wave (mm-wave) massive MIMO heterogeneous cloud radio access networks with limited fronthaul capacity. The coordinated multipoint transmission is applied in each RRHC for cancelling the intra-cluster interference. To avoid the inter-tier interference, distinct bandwidths are allocated to macro base station and RRHs. Following this, we formulate a bandwidth and power allocation optimization problem to maximize the downlink weighted sum rate of the system subject to per-RRHC power and fronthaul capacity constraints, which is a non-convex optimization problem and is difficult to directly solve. Next, we fix the bandwidth allocation and the original problem can be divided into two independent optimization problems, i.e., the weighted sum rate maximization problems of MUs and RRH users, respectively. For the former, the convex optimization technique can be used to solve it. As for the latter, a two-loop iterative algorithm is proposed to deal with it. Specifically, we propose the price-based outer iteration to control the fronthaul capacity and the weighted minimum mean square error-based inner iteration to obtain the power allocation. To this end, a 1-D search method is adopted to find the optimal bandwidth allocation. Finally, numerical results are conducted to verify the effectiveness of the proposed algorithms under different parameters.

Original languageEnglish
Article number8467547
Pages (from-to)7691-7703
Number of pages13
JournalIEEE Transactions on Wireless Communications
Issue number11
Publication statusPublished - Nov 2018

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


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