Xiujun Zhang

Sparse Bayesian learning based user detection and channel estimation for SCMA uplink systems

Sparse code multiple access (SCMA), as a new non-orthogonal multiple-access technique, is capable to achieve massive connectivity and grant-free transmission in wireless radio access. In order to support decoding of signal from simultaneous accessing users, active users detection and channel estimation is needed, which requires significant pilot overhead, especially in channels with relative small coherent frequency / time. In this paper, an algorithm based on the framework of sparse Bayesian learning (SBL) is proposed to reduce the requirement of pilots overhead. The effectiveness of the proposal is described and analyzed, meanwhile the complexity is evaluated. Numerical simulations are performed to substantiate the performance of the proposed algorithm.

Energy Efficient Sleep Mode Activation Scheme for Small Cell Networks

Small cells deployed over the existing macrocell network reduce the access distance and thus offer an energy-efficient solution to provide high data rate coverage. However, dense deployment of small cells may cause energy waste under low load conditions. To cope with this issue, power saving techniques for small cell networks need to be carefully investigated. Invoking a sleep mode is one of the most promising techniques, which allows a small cell base station (SBS) without active users to enter a low power mode and switch to an active mode when required. When a user is within the coverages of several SBSs, the SBS with the best channel condition should be activated by comparing the channel fading from different SBSs to the user. Selecting the right SBS for an active user is challenging because the sleeping SBSs do not send or receive radio frequency signals for channel estimations. In this paper, we propose an energy efficient sleep mode activation scheme for small cell networks, in which the core network activates the sleeping SBS with the smallest large-scale channel fading to the active user. This scheme makes use of channel measurements in advance and adopts spacial interpolation to estimate the large-scale channel fading from sleeping SBSs to the active user. Simulation results show that the spacial interpolation can effectively estimate the large- scale channel fading, and the proposed sleep activation scheme can effectively save transmit power and hence improve the overall network energy- efficiency.

Deployment of 5G networking infrastructure with machine type communication considerations

Designing optimal strategies to deploy small cell stations is crucial to meet the quality-of-service requirements in next-generation cellular networks with constrained deployment costs. In this paper, a general deployment framework is proposed to jointly optimize the locations of backhaul aggregate nodes, small base stations, machine aggregators, and multi-hop wireless backhaul links to accommodate both human-type and machine-type communications. The goal is to provide deployment solutions with best coverage performance under cost constraints. The formulated problem is shown to be a multi-objective integer programming for which it is challenging to obtain the optimal solutions. To solve the problem, a heuristic algorithm is proposed by combining Lagrangian relaxation, the weighted sum method, the e-constraint method and tabu search to obtain both the solutions and bounds, for the objective function. Simulation results show that the proposed framework can provide solutions with better performance compared with conventional deployment models in scenarios where available fiber connections are scarce. Furthermore, the gap between obtained solutions and the lower bounds is quite tight.

User detection and channel estimation for SCMA uplink system in dispersive channel

Sparse code multiple access (SCMA) is a new non-orthogonal multiple-access technique in future wireless networks. In SCMA uplink burst transmission, user detection and channel estimation require significant pilot overhead. Dispersive channels with relative small coherent frequency / time, as well as fading diversity techniques, both lead to a result that multiple fading blocks are taken during one transmission. In this paper, a new method of separating SCMA user detection and channel estimation among different fading blocks in dispersive channels is proposed to reduce pilot overhead. Further more, according to the sparsity of SCMA codebooks, a new mapping pattern from SCMA layers to physical resources is proposed to improve channel estimation performance with given pilots. The effectiveness of the proposal are described and analyzed, meanwhile the complexity is evaluated. Numerical simulations are performed to substantiate the performance of the proposed algorithm.

A Low-Complexity Pilot Reuse Scheme to Increase the Throughput of Massive MIMO

Pilot reuse (PR) in each cell has been proposed to reduce the pilot overhead and improve the throughput of massive multiple-input multiple-output systems. Since PR can introduce interference into channel estimation, several pilot scheduling schemes have been developed to alleviate this problem. However, current schemes have high computational complexity. In this paper, we try to design a low-complexity PR scheme making full use of the channel angle-of- arrival (AOA) information. First we point out that the pilot interference may remain severe even though the AOAs of users reusing pilots are non- overlapping, then an additional criterion is proposed to guide PR. We also develop a method based on the spatial filtering to estimate the channel AOA cosine interval, and develop a PR scheme with the criterion. Simulation results show that the pilot interference can be mainly confined to be a very low level under the proposed PR scheme, and the system throughput can be greatly improved compared to the conventional massive MIMO system.

Optimization of AP placement in indoor fingerprint positioning

There has been significant development in indoor positioning techniques based on location fingerprinting in wireless networks. AP placement has an impact on indoor fingerprint positioning precision. In this study, a max-min RSS distance method to optimize AP placement in KNN fingerprint positioning is proposed for location accuracy and the simulation results are presented based on IEEE 802.11 TGn channel models.

Pilot allocation for doubly selective channel estimation in OFDM systems

This paper investigates deterministic pilot allocation for compressed sensing (CS) based channel estimation of doubly selective channel in Orthogonal Frequency Division Multiplexing (OFDM) systems. Based on minimizing the coherence of submatrix of two-dimensional Discrete Fourier Transform (2D-DFT) matrix, the optimum pilot location criterion for greedy reconstruction methods is derived. However, it is difficult to find such optimum pilot location set. A greedy method is proposed to search a suboptimal pilot allocation solution. Whats more, considering the special structure of doubly selective channel, an improved reconstruction method based on Orthogonal Matching Pursuit (OMP) is proposed. Simulation results demonstrate a significant improvement of channel estimation performance by using the proposed pilot allocation and the improved reconstruction method.

An anti-overflow control method of state metrics for high throughput Turbo decoder

Since the dynamic range of state metrics is limited due to the finitude of their quantization, it is needed to take an anti-overflow operation in the implementation of Turbo decoder. In traditional methods, plenty of calculations should be done for the anti-overflow protection in a single cycle, which greatly restricts the actual running clock frequency, thus to bring a strong impact on the final decoding throughput. In this paper, a novel anti-overflow method is proposed, to compare with the conventional methods, the proposed method can significantly increase the running clock frequency and achieve higher decoding throughput without losing any decoding performance.

Dynamic on/off control of wireless small cells with heterogeneous backhauls

Deploying small cells is one of the most promising techniques to improve cellular network capacity. However, under a dense deployment of small cells, effective strategies should be proposed to control the network power expenditure. In this paper, a general framework for on/off control of small cells is proposed for a cellular network with heterogeneous backhauls. The proposed framework jointly considers power consumption over the access links and the wireless backhaul links. The goal is to satisfy the user demand with minimum total power consumption from both the macro base station (BS) and small base stations (SBSs). The formulated problem is shown to be a non-linear integer programming for which it is challenging to obtain a closed-form optimal solution. To solve the problem, a simulated annealing based algorithm is proposed to transform the problem into a series of set covering problems. Then, a tabu search algorithm is used solve the NP-hard set covering problem. Simulation results show that the proposed approach can reduce the energy consumption up to 12% compared with a probability based control algorithm where each SBS stays active based on a pre-determined probability.

Measurement-based analysis of channel capacity in aircraft cabin distributed MIMO system

The aircraft cabin wireless network recently attracts more attentions from academia and industry. In this paper, we investigate the channel capacity in the cabin distributed multiple-input multiple-output (D-MIMO) system on the basis of measurement data collected in an MD-82 aircraft. The channel measurements are conducted at 2.4 GHz and 3.52 GHz by using a wideband MIMO channel sounder. Two different measurement scenarios, i.e., cabin aisle and cabin seat table are chosen as line-of-sight (LoS) and obstructed LoS (OLoS) environments for channel capacity studies. Two kinds of channel capacity metrics, i.e., ergodic capacity and outage capacity are characterized from the measured channel-impulse-response (CIR) data in order to explore the channel characteristics in aircraft. In each scenario, it is found that D-MIMO/distributed multiple-input single-output (D-MISO) systems can achieve significant capacity gains in comparison with single-input single-output (SISO) system. Regarding the cabin spatial position impact on capacity, measurement results further indicate that the channel capacity in cabin seat table environment decreases due to the obstruction of seat backrests. Through the comparisons of two frequency scenarios, we also find that channel capacity increases when frequency becomes larger. All these findings could provide practical references to the future applications of D-MIMO in aircraft cabin wireless systems.