Joint Millimeter-Wave Fronthaul and OFDMA Resource Allocation in Ultra-Dense CRAN

Abstract

Abstract-Ultra-dense (UD) wireless networks and cloud radio access networks (CRAN) are two promising network architectures for the emerging fifth-generation (5G) wireless communication systems. By jointly employing them, a new appealing network solution is proposed in this paper, termed UD-CRAN. In a UD-CRAN, millimeter-wave (mmWave) wireless fronthaul is preferred for information exchange between the central processor and the distributed remote radio heads (RRHs), due to its lower cost and higher flexibility in deployment, compared to fixed optical links. This motivates our study in this paper on the downlink transmission in a mmWave fronthaul enabled, orthogonal frequency division multiple access (OFDMA) based UD-CRAN. In particular, the fronthaul is shared among the RRHs via time division multiple access (TDMA); while the RRHs jointly transmit to the users on orthogonal frequency subchannels using OFDMA. The joint resource allocation over the TDMA-based mmWave fronthaul and OFDMA-based wireless transmission is investigated to maximize the weighted sum rate of all users. Although the problem is non-convex, we propose a Lagrange duality based solution, which can be efficiently computed with good accuracy. To further reduce the complexity, we also propose a greedy search based heuristic, which achieves close to optimal performance under practical setups. Finally, we show the significant throughput gains of the proposed joint resource allocation approach compared to other benchmark schemes by simulations.Index Terms-Cloud radio access network, orthogonal frequency division multiple access, resource allocation, ultra-dense network, millimeter-wave fronthaul.

Green Communication for NOMA-Based CRAN

“…The coverage radius of each RRH is 200 meters, and the distance between the RRH and the CP is 1500 meters. The mmWave channel is centered at 73 GHz with a bandwidth of W AC =50 MHz and the path loss is modeled as 69.7 + 24 log 10 (d) dB, where d denotes the distance (meter) [8], [25]. The wireless fronthaul channel is centered at a frequency of 2 GHz with a bandwidth of W FH = 10 MHz, and the path loss is modeled as 120 + 30 log 10 (d) dB, where d denotes the distance (kilometer) [26].…”

“…In [8], the authors apply the millimeter-wave (mmWave) wireless fronthaul links and orthogonal frequency division multiple access (OFMDA)-based access links. Then, a joint power and subcarrier allocation algorithm is proposed to maximize the weighted sum rate of the devices.…”

“…Although the above works consider the wireless fronthaul links, the fronthaul capacity are usually assumed as fixed (e.g., [16], [17]). In addition, the transmit power of the CP is also considered a constant in [8]. [18] only considers the system throughput and does not involve EE.…”

“…It is clear that [8]- [18] only focus on the resource allocation in CRAN. As a significant technique candidate for the future IoT networks, NOMA-based CRAN has been not obtained the enough attention.…”

“…In CRAN, the complicated signal processing and resource allocation are conducted by cloud with a central processor (CP), and RRHs only take charge of the radio frequency processing. Based on this, the low-complexity RRHs and centralized resource allocation simplify the system management and enhance the system performance [8]. Therefore, the combination of the NOMA and CRAN to form a NOMA-based CRAN (as shown in Fig.…”