FFR 기반의 Femtocell 네트워크를 위한 적응 주파수 자원 할당 방법

Device-to-Device (D2D) communications underlaying cellular networks can improve the network capacity and spectrum efficiency by sharing the cellular resources in the direct-transmission mode. However, the stringent interference between D2D and cellular systems can seriously repress the overall performance improvement. In this paper, we aim to solve this dilemma by applying the concept of differentiated priority into the resources sharing problem between the D2D pairs and cellular users. Firstly, we modified the conventional partial time-frequency resource allocation scheme to let each D2D pair select its sharing comrades, i.e. the cellular users, based on its own preference list such that less amount of mutually interference can be incurred. Secondly, the differentiated priority scheme is furthered implemented into the cellular users, i.e. the so-called bipartite differentiated priority. Then, the association problem between the D2D pairs and cellular users is solved by using the Gale-Shapley algorithm. The simulation results show that the proposed schemes can greatly enhance the system stability and capacity, while accommodating more D2D pairs.

An LTE-Advanced (LTE-A) Heterogeneous Network (HetNet) constitutes of a macro cell and small cells, where, the former acts as an overlay network and the latter as an underlay network. In HetNet, enabling Carrier Aggregation (CA) usually results in severe downlink interference at small cells from macro cell because of high powered transmissions from macro cell on over-lapping component carriers (co-channels). The intensity of downlink interference is much more profound in HetNet enabled with CA than compared with a single carrier HetNet and ultimately affects the Quality of Service (QoS) of users connected to small cells. Some frequency domain solutions like cross carrier scheduling, soft frequency reuse, and downlink power control have been proposed so far, but they do not provide complete orthogonal transmissions among macro and small cells, leading to adjacent channel interference. Also, a few time domain approaches like Almost Blank Subframe (ABS), dynamic ABS have been proposed in the literature. However, the resource utilization of cells decreases due to high number of ABS assignments in the dense deployment, which also results in low user throughput. In this paper, we propose a combined time domain and frequency domain novel idea for downlink interference control, which is via adaptive Discontinuous Reception (DRX) settings through Multi-Objective optimizations and an optimal carrier allocation scheme, respectively. The proposed idea mitigates the downlink co-channel interference by enabling intermittent data reception at the User Equipment (UE) through adaptive DRX settings, also it utilizes an effective carrier allocation scheme such that users are always allocated to carriers with least interference. The analytical model and simulation results reveal that the proposed idea achieves average gain of 3.5 times w.r.t cell throughput when compared with well-known downlink interference mitigation schemes.

This paper presents a new and simple decoding algorithm for layered space time block codes such as the two independent Alamouti's codes which are also called the double space-time transmit diversity (DSTTD) system. By using group interference suppression and successive interference cancellation, we can treat DSTTD as two independent space-time block codes (STBC). We can then decode both of these STBC's through a simple maximum likelihood (ML) detector with null space-based interference cancellation. We also compare the proposed interference cancellation (IC) scheme with the conventional MMSE IC scheme. The performance of the proposed IC scheme is comparable to that of the MMSE IC scheme while the complexity of the proposed scheme is lower than that of the MMSE IC scheme.

SUMMARYResource allocation in the cloud is becoming more complicated and challenging due to the rising necessities of cloud services. Effective management of virtual resources in the cloud is of large significance since it has a great impact on both the operational cost and scalability of the cloud environment. Nowadays, containers are becoming more popular in this regard due to their characteristics like reduced overhead and portability. Conventional resource allocation schemes are usually modeled for the migration and allocation of virtual machines (VM), as a result; the question may arise on, “how these strategies can be adapted for the management of a containerized cloud”. This work evolves the solution to this issue by introducing a new fitness oriented moth flame algorithm (F‐MFA) for optimizing the allocation of containers. Further in this work, the optimal allocation relies on certain constraints like balanced cluster use, system failure, total network distance (TND), security and threshold distance, and credibility factor as well. In the end, the supremacy of the presented model is computed to the conventional models in terms of cost and convergence analysis.

This paper deals with our investigations into improving the performance of orthogonal frequency division multiple access (OFDMA) system with low computational complexity. In the proposed scheme, by taking attribute of a user channel like channel capacity decrease rate, subcarriers are allocated depending on the individual users' priority. This scheme is high reliable technique by ordering the capacity decrease rate and allocating subcarriers to users depending on the proposed user' priority. Also we apply error-based bit allocation scheme according to channel condition. And to reduce the computational complexity and iterations until reaching a final allocation, simplified adaptation based on bit error rate (BER) is suggested and compared with original algorithm. As the channel evaluation parameter, signal to noise ratio (SNR) estimation method is used. Our proposed scheme is simulated in comparison with a conventional resource allocation scheme. It is shown that proposed method demonstrates better results than the simulated schemes.

Wireless self-backhaul technology is an effective solution to the backhaul bottleneck of 5G Heterogeneous Networks (HetNets). To effectively utilize the spectrum resource as well as reduce the transmission load of backhaul links, we propose a joint Context-aware Data Caching and Resource Allocation (CDCRA) scheme for self-backhauled HetNets aiming at maximizing the total system throughput. Context-aware technology combined with many-to-many matching theory is utilized for data caching in small base stations (SBSs). Then interference management based on graph theory is considered when allocating spectrum resource for both access links and backhaul links. Different comparison schemes are designed to verify the performance of our proposed scheme. Simulation results indicate that the total system throughput is significantly improved by CDCRA scheme comparing with other data caching and resource allocation schemes.

This paper presents a number of key radio resource management strategies across physical (PHY) and medium access control (MAC) layers for reducing base station energy consumption including power efficient link adaptation (LA), exploitation of multi-user diversity and trading bandwidth for energy efficiency. By collectively taking advantage of these radio resource management strategies, a multi-user adaptive power and resource allocation algorithm is proposed to ease the power requirements of a base station, whilst maintaining the same levels of service. The scheduling algorithm is evaluated within a LTE downlink simulator for various traffic load conditions. The results show that the proposed algorithm achieves a significant energy saving over a conventional non-energy aware resource allocation scheme.

Adaptive resource allocation is one of the most challenging tasks for multiuser orthogonal frequency division multiplexing (OFDM) systems. In this paper, two evolutionary approaches, genetic algorithm (GA) and particle swarm optimization (PSO) have been applied for adaptive subcarrier and bit allocations to minimize the overall transmit power of a multiuser OFDM system. Each user will be assigned a number of subcarriers with at least one minimum subcarrier even at the worst case. Then the number of bits and the transmit power level for each subcarrier are calculated. Simulation results show that both the evolutionary approaches outperform the conventional static resource allocation schemes considerably in multiuser scenario. The results further reveal that both the algorithms can handle large allocation of subcarriers without significant performance degradation. However the performance of PSO is found to be better than the GA in terms of execution time, simplicity and convergence.

We study the problem of maximizing the total system throughput under a bit error rate constraint for all users in the uplink of a single-cell synchronous CDMA system. Users realize variable bit rates by using a combination of multicode transmission and adaptive QAM modulation. We assume random signature sequences for all users, and perform an asymptotic analysis. We parametrize each user's resource allocation scheme by two parameters, viz., the number of signatures the user transmits with and the number of signal points in the user's QAM constellation, and optimize the total throughput over this parameter space. We examine four different settings: single-user matched filter (SUMF) and minimum-mean-square error (MMSE) receiver at the base station, with and without maximum power constraints. For a single user system, we describe the jointly optimum number of multicodes and constellation sizes for these four different system models. When multiple users are present, we show that the total throughput is maximized when only one user transmits: with no maximum power constraints this user can be chosen arbitrarily, otherwise it should be the one with the largest SNR. This solution, although optimal in the sense of maximizing the total throughput, is unfair to all but one user: thus, we examine a scheduling mechanism that assigns equal time frames to all users, thus yielding maximum fairness, and discuss the resulting total throughput loss.

The severe interference in full-duplex (FD) cellular network largely degrade the system performance, especially for cell edge users. In this paper, hybrid full/half duplex cellular network which is composed of a mixture of FD and half duplex (HD) base-stations (BSs) is focused. In order to relieve the received inter-cell interference, frequency reuse (FR) is applied. The adopted FR schemes include traditional full FR and two kinds of fractional FR (FFR) named Strict FFR (StFFR) and Soft FFR (SoFFR). Stochastic geometry is adopted to evaluate the system performance. Tractable results of the ergodic rate and coverage probability for different FR schemes are obtained. Through the numerical results, we can observe that full FR and StFFR schemes can improve the user coverage probability at the expense of system spectrum efficiency (SE). SoFFR can improve both the coverage probability and the system SE. The numerical results also show that if the residual Self-interference is not very strong, operating all the BSs in FD mode can achieve the best performance, otherwise, it is better to operate all the BSs in HD mode.

Fractional Frequency Reuse (FFR) is considered to provide enhancement in total throughput and an important reduction of the outage probability in two-tier macrocell-femtocell networks. However the allocation in FFR can create high cross-tier interferences to users located in the boundaries of the various zones. We propose a FFR scheme to alleviate the downlink cross-tier interference for users in these particular zones, joint with a QoS- aware analytical model to derive the blocking probabilities for different cell zones. The optimal parameters for cell channel partitioning in the proposed FFR-scheme are integrated to enhance the proposed system. Numerical results demonstrate the performance enhancement of the proposed joint FFR allocation and admission control scheme. Compared to current FFR and admission control strategies, our scheme permits to increase overall traffic by up to 40 % at cell center and 30 % at cell edge, for any given blocking probability.

This paper investigates the resource allocation schemes for Voice over Internet Protocol (VoIP) traffic under high speed train scenario, in which 2-state VoIP traffic model based on Markov chain is considered. Unlike the full-buffer traffic, in which the transmitter buffer is always full of data to be transmitted, VoIP traffic can be characterized by small packets in regular intervals with tight delay constraints. Considering this, two different resource allocation schemes are discussed in this paper. One is an existing scheme adopting fixed Modulation and Coding scheme (MCS) without packet-bundling, which is commonly used for VoIP scheduling in traditional cellular networks; the other one is our proposed scheme, which uses adaptive MCS with packet-bundling and is suitable for broadband wireless communication under high-speed train scenario. System-level simulation is conducted and the simulation results show that the proposed scheme outperforms the conventional resource allocation scheme in terms of the VoIP outage probability and VoIP capacity under high-speed train scenario.

In this work, the authors derive the optimal signal‐to‐interference‐ratio (SIR) thresholds S t which maximise coverage probability for both fractional frequency reuse (FFR) and soft frequency reuse (SFR) networks with base station locations modelled using Poisson point process. It is analytically shown that for both FFR and SFR, the optimal SIR threshold is equal to the target SIR T , i.e, S t = T . The authors also show that at the optimal SIR threshold, FFR achieves a higher coverage than frequency reuse (1/Δ). Furthermore, for the cases when S t > T and S t < T , FFR achieves a higher coverage than reuse (1/Δ) and reuse 1, respectively. On the other hand, SFR coverage can be higher or lower than reuse (1/Δ) coverage, even when S t = T . However, when S t > T , SFR achieves a higher coverage than reuse 1, and when S t < T , the SFR coverage can be lower than reuse 1 coverage. The FFR and SFR coverages are also compared for a given Δ, and it is shown that FFR achieves a higher coverage than SFR at the optimal value of S t .

In this paper, we design a resource allocation (RA) scheme for the downlink of relay-assisted orthogonal frequency division multiple access cellular networks. Our design goal is to maximize the energy efficiency (EE) with minimal signaling overhead and low computational complexity. To alleviate the signaling overhead of channel information, the proposed scheme allocates the resources in a distributed manner, where each relay station (RS) or base station (BS) individually performs a joint subchannel and power allocation for its subordinate users. To increase the cell throughput, the proposed scheme allows the subchannel reuse among RSs and this enhances the EE performance. The proposed scheme is composed of the resource allocation at RS (RS-RA) and the resource allocation at BS (BS-RA). The RS-RA is formulated as an optimization problem that minimizes the consumed power of RS while reusing as many subchannels as possible among RSs. The optimization objective of BS-RA is to maximize the EE of the cell. Simulation results show that the proposed distributed RA scheme achieves remarkably excellent EE performance with small signaling overhead, comparable with the centralized optimal RA scheme aiming at the EE maximization based on full channel information.

Conventional resource-allocation schemes in orthogonal frequency-division multiple-access (OFDMA) systems consider only one bit-error-rate (BER) requirement. When these schemes are applied to transmit bitstreams with multiple BER requirements, low resource utilization will occur since the target BER has to be the strictest one. We develop a BER-driven resource allocation for generic bitstreams (BRA-G) algorithm by exploiting multiple predetermined target BERs. Then, this scheme is extended to transmission of realistic scalable bitstreams (BRA-SB) where more important (MI) layers possess lower target BERs as compared with less important (LI) layers. The objective here is to maximize the expected quality of all JPEG 2000 (J2K) scalable bitstreams subject to a total power constraint. Instead of using static target BERs for different layers, BRA-SB water-fills over all layers to determine the number of transmit layers and the target BER of each layer simultaneously based on the importance of each layer in terms of reconstructed quality and average channel conditions. Bit-level results show that BRA-SB provides significant image quality improvement over a scheme that ignores the layer's importance in terms of target BER and a BRA-SB-like scheme with static target BERs. A suboptimal algorithm is also proposed to reduce the computational complexity and its performance is close to the optimal one.