292 research outputs found

    Joint Multi-Cell Resource Allocation Using Pure Binary-Integer Programming for LTE Uplink

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    Due to high system capacity requirement, 3GPP Long Term Evolution (LTE) is likely to adopt frequency reuse factor 1 at the cost of suffering severe inter-cell interference (ICI). One of combating ICI strategies is network cooperation of resource allocation (RA). For LTE uplink RA, requiring all the subcarriers to be allocated adjacently complicates the RA problem greatly. This paper investigates the joint multi-cell RA problem for LTE uplink. We model the uplink RA and ICI mitigation problem using pure binary-integer programming (BIP), with integrative consideration of all users' channel state information (CSI). The advantage of the pure BIP model is that it can be solved by branch-and-bound search (BBS) algorithm or other BIP solving algorithms, rather than resorting to exhaustive search. The system-level simulation results show that it yields 14.83% and 22.13% gains over single-cell optimal RA in average spectrum efficiency and 5th percentile of user throughput, respectively.Comment: Accepted to IEEE Vehicular Technology Conference (VTC Spring), Seoul, Korea, May, 201

    Spatial Frequency Scheduling for Uplink SC-FDMA based Linearly Precoded LTE Multiuser MIMO Systems

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    This paper investigates the performance of the uplink single carrier (SC) frequency division multiple access (FDMA) based linearly precoded multiuser multiple input multiple output (MIMO) systems with frequency domain packet scheduling. A mathematical expression of the received signal to interference plus noise ratio (SINR) for the studied systems is derived and a utility function based spatial frequency packet scheduling algorithms is investigated. The schedulers are shown to be able to exploit the available multiuser diversity in time, frequency and spatial domains

    Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks

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    Heterogeneous cloud radio access networks (H-CRANs) are envisioned to be promising in the fifth generation (5G) wireless networks. H-CRANs enable users to enjoy diverse services with high energy efficiency, high spectral efficiency, and low-cost operation, which are achieved by using cloud computing and virtualization techniques. However, H-CRANs face many technical challenges due to massive user connectivity, increasingly severe spectrum scarcity and energy-constrained devices. These challenges may significantly decrease the quality of service of users if not properly tackled. Non-orthogonal multiple access (NOMA) schemes exploit non-orthogonal resources to provide services for multiple users and are receiving increasing attention for their potential of improving spectral and energy efficiency in 5G networks. In this article a framework for energy-efficient NOMA H-CRANs is presented. The enabling technologies for NOMA H-CRANs are surveyed. Challenges to implement these technologies and open issues are discussed. This article also presents the performance evaluation on energy efficiency of H-CRANs with NOMA.Comment: This work has been accepted by IEEE Network. Pages 18, Figure

    Dynamic User Grouping and Joint Resource Allocation with Multi-Cell Cooperation for Uplink Virtual MIMO Systems

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    This paper proposes a novel joint resource allocation algorithm combining dynamic user grouping, multi-cell cooperation and resource block (RB) allocation for single carrier-frequency division multiple access (SC-FDMA) uplink in multicell virtual MIMO systems. We first develop the dynamic multicell user grouping criteria using minimum mean square error (MMSE) equalization and adaptive modulation (AM) with bit error rate (BER) constraint. Then, we formulate and solve a new throughput maximization problem whose resource allocation includes cell selection, dynamic user grouping and RB pattern assignment. Furthermore, to reduce the computational complexity significantly, especially in the case of large numbers of users and RBs, we present an efficient iterative Hungarian algorithm based on user and resource partitions (IHA_URP) to solve the problem by decomposing the large scale problem into a series of small scale sub-problems, which can obtain close-to-optimal solution with much lower complexity. The simulation results show that our proposed joint resource allocation algorithm with dynamic multicell user grouping scheme achieves better system throughput with BER guarantee than fixed user grouping algorithm and other proposed schemes in the literature

    Signal Processing and Learning for Next Generation Multiple Access in 6G

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    Wireless communication systems to date primarily rely on the orthogonality of resources to facilitate the design and implementation, from user access to data transmission. Emerging applications and scenarios in the sixth generation (6G) wireless systems will require massive connectivity and transmission of a deluge of data, which calls for more flexibility in the design concept that goes beyond orthogonality. Furthermore, recent advances in signal processing and learning have attracted considerable attention, as they provide promising approaches to various complex and previously intractable problems of signal processing in many fields. This article provides an overview of research efforts to date in the field of signal processing and learning for next-generation multiple access, with an emphasis on massive random access and non-orthogonal multiple access. The promising interplay with new technologies and the challenges in learning-based NGMA are discussed

    Multiuser Scheduler and FDE Design for SC-FDMA MIMO Systems

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    This paper presents a novel spatial frequency domain packet scheduling and frequency domain equalization (FDE) algorithm for uplink Single Carrier (SC) Frequency Division Multiple Access (FDMA) multiuser MIMO systems. Our analysis model is confined to 3GPP uplink SC-FDMA transmission with Multi-user (MU) Spatial Division Multiplexing (SDM). The results show that the proposed MU-MIMO scheduler in conjunction with the new FDE singificantly increases the maximum achievable rate and improves the bit error rate (BER) performance for the system under consideration
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