Abstract
This paper investigates the achievable per-user degrees-of-freedom (DoF) in multi-cloud based sectored hexagonal cellular networks (M-CRAN) at uplink. The network consists of N base stations (BS) and base band unit pools (BBUP), which function as independent cloud centers. The communication between BSs and BBUPs occurs by means of finite-capacity fronthaul links of capacities with P denoting transmit power. In the system model, BBUPs have limited processing capacity . We propose two different achievability schemes based on dividing the network into non-interfering parallelogram and hexagonal clusters, respectively. The minimum number of users in a cluster is determined by the ratio of BBUPs to BSs, . Both of the parallelogram and hexagonal schemes are based on practically implementable beamforming and adapt the way of forming clusters to the sectorization of the cells. Proposed coding schemes improve the sum-rate over naive approaches that ignore cell sectorization, both at finite signal-to-noise ratio (SNR) and in the high-SNR limit. We derive a lower bound on per-user DoF which is a function of , , and r. We show that cut-set bound are attained for several cases, the achievability gap between lower and cut-set bounds decreases with the inverse of BBUP-BS ratio for irrespective of , and that per-user DoF achieved through hexagonal clustering can not exceed the per-user DoF of parallelogram clustering for any value of and r as long as . Since the achievability gap decreases with inverse of the BBUP-BS ratio for small and moderate fronthaul capacities, the cut-set bound is almost achieved even for small cluster sizes for this range of fronthaul capacities. For higher fronthaul capacities, the achievability gap is not always tight but decreases with processing capacity. However, the cut-set bound, e.g., at , can be achieved with a moderate clustering size.
Highlights
Interference is one of the fundamental obstacles for high data rate communications in current and future cellular networks because of restricting the effect on overall spectral efficiency in bits/sec/Hz/base station
We show that cut-set bound are attained for several cases, the achievability gap between lower and cut-set bounds decreases with the inverse of base band unit pools (BBUP)-base stations (BS) ratio r for μF ≤ 2M irrespective of μBBU, and that per-user degrees of freedom (DoF) achieved through hexagonal clustering can not exceed the per-user DoF of parallelogram clustering for any value of μBBU and r as long as μF ≤ 2M
We ignore it in the current work since the interference is close to the noise level and our focus will be on the sum-capacity of the sectored hexagonal network in the high signal-to-noise ratio (SNR) and the degrees of freedom (DoF) per-user
Summary
Interference is one of the fundamental obstacles for high data rate communications in current and future cellular networks because of restricting the effect on overall spectral efficiency in bits/sec/Hz/base station. We find an efficient way of dividing the network non-interfering parallelogram clusters by silencing mobile users mostly in single sectors of the considered cells; We propose achievability schemes for both parallelogram and hexagonal clusterings and derive lower bounds on per-user DoF for both schemes in a function of fronthaul and BBUP processing capacities and BBUP-BS ratio; We prove that the performance of parallelogram clustering can not be worse than hexagonal clustering for small and moderate fronthaul capacities; We show by simulations that, for high fronthaul capacities, the coding scheme proposed for hexagonal clustering can show better performance than parallelogram clustering if the processing capacity is large enough according to given BBUP-BS ratio. In the finite SNR case, we compare the proposed coding schemes with the following schemes: Naive versions of both schemes where all mobile users in certain cells are deactivated, Interfering versions of both schemes where the network is decomposed into non-overlapping but interfering clusters, An opportunistic scheme where each message is decoded based on the received signals of three neighboring sectors that have the strongest channel gains. An interesting outcome of the finite SNR analysis is that interfering clustering schemes show either close to or better performance than proposed schemes in the finite SNR range under both weak and strong interference regimes; the interfering clusterings can be employed at finite SNR values with minor performance losses, since they may be more convenient for practical systems
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