Thang Xuan Vu

Successive Pilot Contamination Elimination in Multiantenna Multicell Networks

This paper addresses the problem of channel estimation in time-division duplex (TDD) multicell cellular systems, where the performance of such systems is usually bounded by a bottleneck due to pilot contamination. We propose two channel estimation schemes that completely remove pilot contamination. The exact closed-form expression for average mean square error (MSE) of the proposed estimators is derived. More importantly, our proposed estimators do not need to know the second-order statistics of either desired user channels or interfering user channels. Finally, simulated results confirm gains over existing channel estimation schemes.

Adaptive Compression and Joint Detection for Fronthaul Uplinks in Cloud Radio Access Networks

Cloud radio access network (C-RAN) has recently attracted much attention as a promising architecture for future mobile networks to sustain the exponential growth of data rate. In C-RAN, one data processing center or baseband unit (BBU) communicates with users via distributed remote radio heads (RRHs), which are connected to the BBU via high capacity, low latency fronthaul links. In this paper, we study the compression on fronthaul uplinks and propose a joint decompression algorithm at the BBU. The central premise behind the proposed algorithm is to exploit the correlation between RRHs. Our contribution is threefold. First, we propose a joint decompression and detection (JDD) algorithm which jointly performs decompressing and detecting. The JDD algorithm takes into consideration both the fading and compression effect in a single decoding step. Second, block error rate (BLER) of the proposed algorithm is analyzed in closed-form by using pair-wise error probability analysis. Third, based on the analyzed BLER, we propose adaptive compression schemes subject to quality of service (QoS) constraints to minimize the fronthaul transmission rate while satisfying the pre-defined target QoS. As a dual problem, we also propose a scheme to minimize the signal distortion subject to fronthaul rate constraint. Numerical results demonstrate that the proposed adaptive compression schemes can achieve a compression ratio of 300% in experimental setups.

On the Diversity of Network-Coded Cooperation With Decode-and-Forward Relay Selection

In this paper, we study outage probability (OP) and diversity order of a M-source and N-relay wireless network that combines network coding (NC) and relay selection (RS). More specifically, a decode-and-forward (DF) relaying protocol is considered and the network-encoding vectors at the relays are assumed to constitute a maximum distance separable (MDS) code. Single relay selection (SRS) and multiple relay selection (MRS) protocols are investigated, where the best relay and the L best relays forward the network-coded packets to the destination, respectively. An accurate mathematical framework for computing the OP is provided and from its direct inspection the following conclusions on the achievable diversity are drawn: 1) the SRS protocol achieves diversity order equal to two regardless of M and N and 2) the MRS protocol achieves diversity order equal to L + 1 if L <; MandequaltoN + 1 if L ≥ M.These analytical findings are substantiated with the aid of Monte Carlo simulations, which also show that RS provides a better OP than NC based on repetition coding if L ≥ M.

Performance Analysis of Network Coded Cooperation with Channel Coding and Adaptive DF-Based Relaying in Rayleigh Fading Channels

Network Coded Cooperation (NCC) is known to provide full diversity order and high spectral efficiency for uncoded cooperative networks. However, the understanding of NCC applied to signals that have been protected by some Forward Error Correction (FEC) codes is still limited. This letter analyzes the diversity order attainable by NCC with channel coding (Coded-NCC) in a network topology with multiple sources, one relay and in the presence of fast Rayleigh fading. Due to the difficulty of characterizing the exchange of information between the network decoder and the channel decoder, iterative network and channel decoding algorithms are usually studied with the aid of simulations. In this letter, we overcome this limitation by proposing a near-optimal receiver that performs network decoding and channel decoding in a single decoding step of an equivalent super code. An upper bound and a tight approximation of the Bit Error Rate (BER) for all sources are derived. Based on the upper bound, we analytically show that Coded-NCC achieves a diversity order equal to 2f, where f is the minimum distance of the FEC code. This result generalizes those available for cooperative networks in the absence of channel coding (Uncoded-NCC), where the diversity order is equal to 2, as well as those available for coded transmission but without cooperation, where the diversity order is equal to f.

Power Optimization With BLER Constraint for Wireless Fronthauls in C-RAN

Cloud radio access network (C-RAN) is a novel architecture for future mobile networks to sustain the exponential traffic growth thanks to the exploitation of centralized processing. In C-RAN, one data processing center or baseband unit (BBU) communicates with users via distributed remote radio heads (RRHs), which are connected to the BBU via high capacity, low latency fronthaul links. In this letter, we study C-RAN with wireless fronthauls due to their flexibility in deployment and management. First, a tight upper bound of the system block error rate (BLER) is derived in closed-form expression via union bound analysis. Based on the derived bound, adaptive transmission schemes are proposed. Particularly, two practical power optimizations based on the BLER and pair-wise error probability (PEP) are proposed to minimize the consumed energy at the RRHs while satisfying the predefined quality of service (QoS) constraint. The premise of the proposed schemes originates from practical scenarios where most applications tolerate a certain QoS, e.g., a nonzero BLER. The effectiveness of the proposed schemes is demonstrated via intensive simulations.

Performance analysis of relay networks with channel code in low SNR regime

This paper analyzes the performance of relay networks with channel coding in low and medium Signal-to-Noise Ratio (SNR) regime. In particular, we study the three-node relay network in the quasi-static block Rayleigh fading channel plus additive white Gaussian noise. Estimate-and-forward (EF) relay protocol is used. In order to achieve high spectrum efficiency, the relay can either forward the whole or a part of the estimated codeword to the destination. The contributions of the paper are as follows: i) First, we compute an upper bound of the Bit Error Rate (BER) of the proposed scheme. ii) Second, from the upper bound, we derive a so-called instantaneous diversity order in low and medium SNR region which is essential to practical systems. The instantaneous diversity depends on both the amount of information forwarded by the relay and the minimum distance of the channel code. Interestingly, the proposed scheme can achieve full diversity gain in a given SNR region of interest (such as BER ≤ 10-5) while obtaining 32% spectrum efficiency improvement compared to classical relay network under appropriate conditions. The analysis is checked by simulation.

Edge-Caching Wireless Networks: Performance Analysis and Optimization

Edge-caching has received much attention as an efficient technique to reduce delivery latency and network congestion during peak-traffic times by bringing data closer to end users. Existing works usually design caching algorithms separately from physical layer design. In this paper, we analyze edge-caching wireless networks by taking into account the caching capability when designing the signal transmission. Particularly, we investigate multi-layer caching where both base station (BS) and users are capable of storing content data in their local cache and analyze the performance of edge-caching wireless networks under two notable uncoded and coded caching strategies. First, we calculate backhaul and access throughputs of the two caching strategies for arbitrary values of cache size. The required backhaul and access throughputs are derived as a function of the BS and user cache sizes. Second, closed-form expressions for the system energy efficiency (EE) corresponding to the two caching methods are derived. Based on the derived formulas, the system EE is maximized via precoding vectors design and optimization while satisfying a predefined user request rate. Third, two optimization problems are proposed to minimize the content delivery time for the two caching strategies. Finally, numerical results are presented to verify the effectiveness of the two caching methods.

A deep learning approach for optimizing content delivering in cache-enabled HetNet

In ultra-dense heterogeneous networks, caching popular contents at small base stations is considered as an effective way to reduce latency and redundant data transmission. Optimization of caching placement/replacement and content delivering can be computationally heavy, especially for large-scale networks. The provision of both time-efficient and high-quality solutions is challenging. Conventional iterative optimization methods, either optimal or heuristic, typically require a large number of iterations to achieve satisfactory performance, and result in considerable computational delay. This may limit their applications in practical network operations where online decisions have to be made. In this paper, we provide a viable alternative to the conventional methods for caching optimization, from a deep learning perspective. The idea is to train the optimization algorithms through a deep neural network (DNN) in advance, instead of directly applying them in real-time caching or scheduling. This allows significant complexity reduction in the delay-sensitive operation phase since the computational burden is shifted to the DDN training phase. Numerical results demonstrate that the DNN is of high computational efficiency. By training the designed DNN over a massive number of instances, the solution quality of the energy-efficient content delivering can be progressively approximated to around 90% of the optimum.

Coded Caching and Storage Planning in Heterogeneous Networks

Content caching is an efficient technique to reduce delivery latency and system congestion during peak-traffic times by bringing data closer to end users. Existing works on caching usually assume symmetric networks with identical user requests distribution, which might be in contrast to practical scenarios where the number of users is usually arbitrary. In this paper, we investigate a cache-assisted heterogeneous network in which edge nodes or base stations (BSs) are capable of storing content data in their local cache. We consider general practical scenarios where each edge node is serving an arbitrary number of users. First, we derive an optimal storage allocation over the BSs to minimize the shared backhaul throughput for a uncoded caching policy. Second, a novel coded caching strategy is proposed to further reduce the shared backhauls load. Finally, the effectiveness of our proposed caching strategy is demonstrated via numerical results.

On the diversity of partial relaying cooperation with relay selection in finite-SNR regime

This work studies the performance of a cooperative network which consists of two channel-coded sources, multiple relays, and one destination. Due to the spectral efficiency constraint, we assume that a single time slot is dedicated to relaying. Conventional network-coded based cooperation (NCC) selects the best relay which uses network coding to serve the two sources simultaneously. It is shown that NCC, however, only achieves diversity of order two regardless of the number of available relays and the channel code. In this paper, we propose a novel partial relaying based cooperation (PARC) scheme to improve the system diversity in the finite signal-to-noise ratio (SNR) regime. Firstly, closed-form expressions for the system bit error rate (BER) and diversity order of PARC are derived as a function of the operating SNR value and the minimum distance of the channel code. Secondly, we analytically show that the proposed PARC achieves full diversity order in the finite SNR regime, given that an appropriate channel code is used. Finally, numerical results verify our analysis and demonstrate a large SNR gain of PARC over NCC in the SNR region of interest.