Jinkyu Kang

Fronthaul Compression and Precoding Design for C-RANs Over Ergodic Fading Channels

This paper investigates the joint design of fronthaul compression and precoding for the downlink of cloud radio access networks (C-RANs). In a C-RAN, a central unit (CU) controls a cluster of radio units (RUs) through low-latency fronthaul links. Most previous works on the design of fronthaul compression and precoding assume constant channels and instantaneous channel state information (CSI) at the CU. This paper, in contrast, concentrates on a more practical scenario with block-ergodic channels and considers either instantaneous or stochastic CSI at the CU. Moreover, the analysis encompasses two types of CU-RU functional splits at the physical layer, which we refer to as compression-after-precoding (CAP) and compression-before-precoding (CBP). With the CAP approach, which is the standard C-RAN solution, all baseband processing is done at the CU. With the CBP scheme, channel encoding and precoding are instead performed at the RUs: The CU does not perform precoding but rather forwards separately the information messages of a subset of mobile stations (MSs) along with the compressed precoding matrices to each RU. Optimization algorithms over fronthaul compression and precoding for both CAP and CBP are proposed, which are based on a stochastic successive upper bound minimization (SSUM) approach. Numerical results yield insights into the optimal RU-CU functional split for C-RANs. As a general conclusion, the relative advantages of the two functional splits depend on the interplay between the enhanced interference management abilities of CAP, particularly for dense networks, and the lower fronthaul requirements of CBP in terms of precoding information overhead, particularly for large coherence periods and with stochastic, rather than instantaneous, CSI.

Design of user clustering and precoding for downlink non-orthogonal multiple access (NOMA)

In this paper, we propose a novel user clustering algorithm for non-orthogonal multiple access (NOMA) considering the channel correlation between users and the channel gain. We also adopt sum-rate maximization approach to find an optimal precoding matrix in the multi-user multiple-input-multiple-output (MU-MIMO) setup after the user clustering. Grouping two users in a single beam to serve users in a non-orthogonal fashion raises multi-user interference (MUI). To tackle this problem, the clustering algorithm considers the channel correlation to select users aligned with same direction. Furthermore, the channel gain is also reflected in the clustering algorithm to enhance signal-to-interference-plus-noise ratio (SINR) inspired by the fact that the optimal precoding matrix is less sensitive to channel direction. Optimization algorithm over the precoding matrix is proposed based on Majorization Minimization (MM) approach for a non-convex objective function. We demonstrate the superiority of the proposed schemes comparing with conventional ones through numerical results.

Minimizing transmit power for cooperative multicell system with massive MIMO

We consider the problem of designing transmit beamformer and power for downlink cooperative base-station (BS) system with a large antenna arrays. Since the design of the beamforming vector at the transmitter requires high computational complexity, in a large antenna arrays, we utilize the zero-forcing transmit beamformer, which is the simplest form and the optimal performance in a large antenna arrays. Therefore, this paper focuses on the design of power allocation with fixed transmit beamformer for minimizing the transmit power while meeting target signal-to-interference-and-noise-ratio (SINR) of each user and power constraints. We consider two scenarios according to the power constraints of cooperative BSs. One scenario is the sum power constraint on the cooperative base-stations. In this case, the cooperative BSs share the total available transmit power. However, each BS exists a maximum available transmit power in practical implementations. Thus, we consider a more realistic per BS power constraints.We proposed the solution strategies for both scenarios: For the sum power constraint case, a simple intuitive solution, where the power is allocated without regard to the power constraint until the SINR constraints is satisfied, is presented. For the per BS power constraints case, we use the properties of a large antenna arrays to find the solution of closed form. We also demonstrate, via numerical simulation, the performance of proposed strategy is convergent to the optimal performance which is achieved by using the iterative algorithm.

Layered Downlink Precoding for C-RAN Systems With Full Dimensional MIMO

The implementation of a cloud radio access network (C-RAN) with full dimensional (FD) multiple-input multiple-output (MIMO) is faced with the challenge of controlling the fronthaul overhead for the transmission of baseband signals as the number of horizontal and vertical antennas grows larger. This paper proposes to leverage the special low-rank structure of the FD-MIMO channel, which is characterized by a time-invariant elevation component and a time-varying azimuth component, by means of a layered precoding approach, to reduce the fronthaul overhead. According to this scheme, separate precoding matrices are applied for the azimuth and elevation channel components, with different rates of adaptation to the channel variations and correspondingly different impacts on the fronthaul capacity. Moreover, we consider two different central unit (CU)–radio unit (RU) functional splits at the physical layer, namely, the conventional C-RAN implementation and an alternative one in which coding and precoding are performed at the RUs. Via numerical results, it is shown that the layered schemes significantly outperform conventional nonlayered schemes, particularly in the regime of low fronthaul capacity and a large number of vertical antennas.

Secure beamforming and self-energy recycling with full-duplex wireless-powered relay

In this paper, we investigate a two-hop full-duplex wireless-powered relaying system consists of a source, a relay, and a destination in the presence of a passive eavesdropper. The relay assists the transmission of confidential information from the source to the destination, while simultaneously harvesting the energy with time switching scheme by the radio-frequency (RF) signals. Our goal is to maximize the physical-layer security under harvested energy constraints by designing the full-duplex wireless-powered relay, whose two relaying strategies are considered, namely amplify-and-forward (AF) and decode-and-forward (DF). The relay beamforming vector design is proposed for AF protocol, and is jointly optimized with the time ratio parameter in the case of DF protocol to maximize the physical-layer security under harvested energy constraints. Moreover, for the simultaneous energy and secure message transfer at the relay, a two-phase method is provided, which enables the relay to avoid the self-interference caused by full-duplex operation, and also to harvest the energy from the self-interference. The proposed algorithmic solutions leverage the rank relaxation, Majorization-Minimization (MM) programming, and line search method. Numerical results show that the proposed full-duplex relaying system outperforms the half-duplex relaying system in energy harvesting. Moreover, the trade-off between AF and DF protocols according to the occurrence probability of non-zero secrecy rate can be observed in terms of physical-layer security.

Joint Resource Allocation for Throughput Enhancement in Cognitive Radio Femtocell Networks

In cognitive radio femtocell network (CRFN), secondary users (SUs) cooperatively sense a spectrum band to decide the presence of primary network. However, this sensing overhead generally degrades the throughput performance. The prior work, to resolve this problem, proposed algorithms either to decrease the time spent in sensing or to decrease the number of SUs participating in sensing. In this paper, we propose a joint resource allocation (RA) strategy considering the time and energy consumed for spectrum sensing to maximize the throughput while satisfying the target detection performance in CRFN. Furthermore, to reduce the resources used in spectrum sensing additionally, we also adopt the right censored order statistics based cooperative spectrum sensing scheme, which produces the criterion for deciding the set of reporting SUs. By so jointly designing the time and energy for sensing, the proposed joint RA scheme provides the improvement of spectral efficiency. Through simulation results, it is shown that the proposed joint RA scheme exhibits the enhanced performance over the conventional ones in terms of total throughput of secondary networks.

Identification of Non-Ideal Receiver Condition for Orbital Angular Momentum Transmission

Although orbital angular momentum (OAM) was first introduced for optical communications, it is drawing attention as a new transmission technique for millimeter wave communication. Due to the additional orthogonal transmit dimension by photon OAM, the theoretical throughput can increase dramatically with various OAM modes. In practice, since OAM by uniform circular arrays (UCAs) has the implementation problem such as twisted axis between transmitter and receiver, the performance degradation happens frequently. Hence, this paper investigates the imperfect receiver condition and the effect of this problem. In particular, the off-axis and non-parallel location problems are focused. Here, the capacity with inter-mode interference (IMI) of OAM is first considered and the receiver compensation method is proposed. Numerical results show that the throughput after compensation is better than that without compensation.

Cooperative spectrum sensing in non-time-slotted full duplex cognitive radio networks

In this paper, we consider the cooperative spectrum sensing (CSS) in the non-time-slotted full duplex cognitive radio (FDCR) networks. In the non-time-slotted cognitive radio (CR) networks, the primary user can change its activity during the transmission duration in contrast with the time-slotted CR networks. We analytically derive the collision probability and the outage probability for the two operation modes of the secondary user under the CSS in non-time-slotted FDCR networks. We then turn to determine the optimum decision threshold for the energy detector at each secondary user to maximize the average throughput subject to a constraint on the outage probability of primary user. In numerical results, we demonstrate and analyze the impact of CSS in the non-time-slotted FDCR networks.

On the Trade-Off Between Computational Load and Reliability for Network Function Virtualization

Network function virtualization enables the “softwarization” of network functions, which are implemented on virtual machines hosted on commercial off-the-shelf servers. Both the composition of the virtual network functions into a forwarding graph (FG) at the logical layer and the embedding of the FG on the servers need to consider the less-than-carrier-grade reliability of COTS components. This letter investigates the tradeoff between end-to-end reliability and computational load per server via the joint design of VNF chain composition (CC) and FG embedding (FGE) under the assumption of a bipartite FG that consists of a controller and regular VNFs. Evaluating the reliability criterion within a probabilistic model, analytical insights are first provided for a simplified disconnected FG. Then, a block coordinate descent method based on mixed-integer linear programming is proposed to tackle the joint optimization of CC and FGE. Via simulation results, it is observed that a joint design of CC and FGE leads to substantial performance gains compared with separate optimization approaches.

Joint precoding and fronthaul optimization for C-RANs in ergodic fading channels

This work investigates the joint design of fronthaul compression and precoding for the downlink of Cloud Radio Access Networks (C-RANs). The main goal is that of bringing insight into an aspect of the optimal functional split between Radio Units (RUs) and Central Unit (CU), namely: where should precoding be performed? Unlike previous works, we tackle this issue for a practical scenario with block-ergodic channels and either instantaneous or stochastic Channel State Information (CSI) at the CU. Optimization algorithms over fronthaul compression and precoding are proposed that are based on a stochastic successive upper-bound minimization approach. Via numerical results, the relative merits of two strategies, in which precoding is carried out at the CU or at the RUs, are evaluated as a function of system parameters such as fronthaul capacity and channel coherence time under either instantaneous or stochastic CSI at the CU.