Decentralized Fair Scheduling in Two-Hop Relay-Assisted Cognitive OFDMA Systems

In this paper, we consider a two-hop relay-assisted cognitive downlink OFDMA system (named as secondary system) dynamically accessing a spectrum licensed to a primary network, thereby improving the efficiency of spectrum usage. A cluster-based relay-assisted architecture is proposed for the secondary system, where relay stations are employed for minimizing the interference to the users in the primary network and achieving fairness for cell-edge users. Based on this architecture, an asymptotically optimal solution is derived for jointly controlling data rates, transmission power, and subchannel allocation to optimize the average weighted sum goodput where the proportional fair scheduling (PFS) is included as a special case. This solution supports decentralized implementation, requires small communication overhead, and is robust against imperfect channel state information at the transmitter (CSIT) and sensing measurement. The proposed solution achieves significant throughput gains and better user-fairness compared with the existing designs. Finally, we derived a simple and asymptotically optimal scheduling solution as well as the associated closed-form performance under the proportional fair scheduling for a large number of users. The system throughput is shown to be $\mathcal{O}\left(N(1-q_p)(1-q_p^N)\ln\ln K_c\right)$, where $K_c$ is the number of users in one cluster, $N$ is the number of subchannels and $q_p$ is the active probability of primary users.Comment: 29 pages, 9 figures, IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSIN

Outage Efficient Strategies for Network MIMO with Partial CSIT

We consider a multi-cell MIMO downlink (network MIMO) where $B$ base-stations (BS) with $M$ antennas connected to a central station (CS) serve $K$ single-antenna user terminals (UT). Although many works have shown the potential benefits of network MIMO, the conclusion critically depends on the underlying assumptions such as channel state information at transmitters (CSIT) and backhaul links. In this paper, by focusing on the impact of partial CSIT, we propose an outage-efficient strategy. Namely, with side information of all UT's messages and local CSIT, each BS applies zero-forcing (ZF) beamforming in a distributed manner. For a small number of UTs ($K\leq M$), the ZF beamforming creates $K$ parallel MISO channels. Based on the statistical knowledge of these parallel channels, the CS performs a robust power allocation that simultaneously minimizes the outage probability of all UTs and achieves a diversity gain of $B(M-K+1)$ per UT. With a large number of UTs ($K \geq M$), we propose a so-called distributed diversity scheduling (DDS) scheme to select a subset of \Ks UTs with limited backhaul communication. It is proved that DDS achieves a diversity gain of B\frac{K}{\Ks}(M-\Ks+1), which scales optimally with the number of cooperative BSs $B$ as well as UTs. Numerical results confirm that even under realistic assumptions such as partial CSIT and limited backhaul communications, network MIMO can offer high data rates with a sufficient reliability to individual UTs.Comment: 26 pages, 8 figures, submitted to IEEE Trans. on Signal Processin

A Survey of Downlink Non-orthogonal Multiple Access for 5G Wireless Communication Networks

Accepted by ZTE CommunicationsAccepted by ZTE CommunicationsAccepted by ZTE CommunicationsAccepted by ZTE CommunicationsAccepted by ZTE CommunicationsNon-orthogonal multiple access (NOMA) has been recognized as a promising multiple access technique for the next generation cellular communication networks. In this paper, we first discuss a simple NOMA model with two users served by a single-carrier simultaneously to illustrate its basic principles. Then, a more general model with multicarrier serving an arbitrary number of users on each subcarrier is also discussed. An overview of existing works on performance analysis, resource allocation, and multiple-input multiple-output NOMA are summarized and discussed. Furthermore, we discuss the key features of NOMA and its potential research challenges

Ultra Dense Small Cell Networks: Turning Density into Energy Efficiency

In this paper, a novel approach for joint power control and user scheduling is proposed for optimizing energy efficiency (EE), in terms of bits per unit energy, in ultra dense small cell networks (UDNs). Due to severe coupling in interference, this problem is formulated as a dynamic stochastic game (DSG) between small cell base stations (SBSs). This game enables to capture the dynamics of both the queues and channel states of the system. To solve this game, assuming a large homogeneous UDN deployment, the problem is cast as a mean-field game (MFG) in which the MFG equilibrium is analyzed with the aid of low-complexity tractable partial differential equations. Exploiting the stochastic nature of the problem, user scheduling is formulated as a stochastic optimization problem and solved using the drift plus penalty (DPP) approach in the framework of Lyapunov optimization. Remarkably, it is shown that by weaving notions from Lyapunov optimization and mean-field theory, the proposed solution yields an equilibrium control policy per SBS which maximizes the network utility while ensuring users' quality-of-service. Simulation results show that the proposed approach achieves up to 70.7% gains in EE and 99.5% reductions in the network's outage probabilities compared to a baseline model which focuses on improving EE while attempting to satisfy the users' instantaneous quality-of-service requirements.Comment: 15 pages, 21 figures (sub-figures are counted separately), IEEE Journal on Selected Areas in Communications - Series on Green Communications and Networking (Issue 2