Low Feedback Overhead Research Articles

Compressed Retransmission for CBG-HARQ

Code block group (CBG) based hybrid automatic repeat request (HARQ) has the advantage of low feedback overhead, but the drawback is the relatively poor transmission efficiency. This letter aims to improve the transmission efficiency of CBG-based HARQ. Based on the fact that, during the retransmission phase, the receiver already has the a prior information of the erroneous codewords, we propose a new scheme to exploit the redundancy. Specifically, all codewords corresponding to the erroneous CBG are linearly compressed into multiple compressed codewords which are transmitted over the channel instead of all corresponding ones. Simulation results show that the proposed compressed CBG-HARQ can achieve a significant higher throughput than the existing group-based HARQ schemes with only one bit feedback overhead at the cost of a marginal increase in complexity.

Sliding-Window-Based RNC Scheme in UAV Multicasting: Performance Analysis and Network Optimization

Unmanned aerial vehicles (UAVs)-enabled multicasting network has attracted significant attention in recent years. However, there are still some disadvantages of existing multicasting schemes used in these systems, such as low transmission efficiency and high feedback overhead. Accordingly, we propose a sliding coding window (SCW)-based random network coding (SCWRNC) scheme for a UAV multicasting network where one UAV base station is dispatched to the multicast data stream to multiple user equipments (UEs). The proposed scheme includes an SCW scheduling original packets for encoding, a lower triangular coding structure enabling UEs to decode out information even without receiving a full set of coded packets, and a feedback-compete mechanism requiring only one UE to send feedback information. The packet scheduling process is described as a five-tuple Markov decision process. Then, we give a theoretical analysis of the proposed scheme, based on which the sliding steps of SCW and the UAV hovering location are jointly optimized to maximize the system throughput. The optimal sliding steps are obtained by applying the Greedy scheduling technique, while the UAV optimal position is obtained by minimizing the maximum outage probability of all UEs. Furthermore, we also propose a flexible feedback mechanism, which enables more than one UE to send feedback for systems with sufficient resources and a “F-SCWRNC” scheme for systems where no UE is allowed to send feedback. Numerical results show that both the proposed SCWRNC scheme and F-SCWRNC scheme could achieve significant throughput gain over the existing ones.

Utilization of Beam Signatures Supporting High User Mobility With Extremely Low Feedback Overhead

Utilization of Beam Signatures Supporting High User Mobility With Extremely Low Feedback Overhead

Channel Feedback in TDD Massive MIMO Systems With Partial Reciprocity

It is widely believed that the channel reciprocity holds in time division duplexing (TDD) massive multiple-input multiple-output (MIMO) systems, so the uplink channel feedback is unnecessary. However, due to the constraint of transmission power and hardware complexity, users may use more receiving antennas than transmitting antennas in practical wireless communication systems. In this practical yet important scenario, only partial channel reciprocity holds, and thus channel feedback is still required in TDD massive MIMO systems. Unfortunately, this important topic has not been investigated in the literature. To fill in this gap, we propose an angle-domain support (ADS) based channel feedback scheme for TDD massive MIMO systems with unequal number of receiving and transmitting antennas. Firstly, by utilizing the angle-domain channel sparsity, we illustrate that a small number of elements in angle-domain channel, which are indexed by ADS, can capture the most power of the channel. Then, we propose the base station (BS) can obtain full downlink channel by decomposing the channel into two parts: the ADS and the low-dimensional angle-domain representation indexed by the ADS. At first, due to the partial channel reciprocity, the ADS is obtained by an angle-domain windows based support detection method at the BS without channel feedback. Then, the low-dimensional angle-domain representation indexed by the ADS is quantized and fed back to the BS. Theoretical analysis and simulation results demonstrate that the proposed scheme can achieve the near-optimal achievable sum-rate performance with low channel feedback overhead.

A novel channel prediction method for MIMO‐OFDM in high‐speed environment

The OFDM system with multiple transceiver antennas is attractive to increase the spectrum or energy efficiency. Depending on the channel state information (CSI), precoding techniques offer array and multiplexing gain in such systems. However, if terminal equipment is fast moving, the CSI feedback would be outdated when it is applied to data transmission. This paper proposes a novel channel prediction method applicable for high-speed environment. Benefiting from the proposed structure, this method greatly improves the prediction accuracy, and meanwhile retains the low feedback overhead. Numerical results show that the performance of the proposed method outperforms conventional precoding methods in high-speed scenarios.

FlexVi: PHY Aided Flexible Multicast for Video Streaming over IEEE 802.11 WLANs

Wireless video multicast over IEEE 802.11 WLANs is a viable approach to bridging the gap between limited wireless resources and the ever-increasing mobile video traffic demand. However, existing wireless multicast mechanisms have several limitations, such as low spectral efficiency, high feedback overhead, and lack of consideration of the frame aggregation feature of current WLANs. In this paper, we propose FlexVi, a flexible wireless multicast solution for efficient video streaming over WLANs. Considering the frame aggregation of the current WLANs, FlexVi allows an access point to dynamically adjust the data rate on the basis of three factors: available wireless bandwidth, heterogeneity of the channel qualities among the clients, and the priorities among the video frames in terms of video quality. In addition, by harnessing the orthogonality of the subcarriers in the orthogonal frequency division multiplexing, FlexVi enables multiple clients to deliver their feedback to an access point simultaneously without collision, which results in very low feedback overhead. We verified the feasibility of FlexVi through experiments on a software defined radio platform. We also conducted an extensive simulation study and found that FlexVi outperforms the latest wireless multicast mechanisms.

Entropy Loading Design for the MIMO-OFDM Visible Light Communication System Using the OCT Precoding Technique

In this paper, an orthogonal circulant matrix transform (OCT) precoding technique is proposed to combine with the entropy loading in the multiple-input multiple-output and orthogonal frequency division multiplexing (MIMO-OFDM) visible light communication (VLC) system where the space-time coding (STBC) is chosen for its robustness to the channel correlation. Benefitting from the OCT precoding technique, the uniform signal-to-noise ratio (SNR) among all the subchannels can be achieved. As a result, only one SNR value is required to be fed back, and the same distribution matcher is employed during probabilistic shaping (PS), which means much lower feedback overhead and system complexity than the conventional entropy loading scheme. Experimental results show that the OCT precoding does not cause the system performance loss where the achievable information rate (AIR) of the proposed system is comparable with the conventional system without precoding. With an available bandwidth of ∼25 MHz, the proposed scheme can realize the AIR of 50.75 Mb/s at the expense of 0.45% average forward error correction (FEC) overhead (OH).

Two Timescale Robust Energy-Efficient Precoding for Dual-Polarized MIMO Systems

In this work, we investigate in depth the two timescale robust system energy efficiency (EE) precoding design for the multiuser dual-polarized multiple-input multiple-output (MIMO) system. To achieve good performance, low feedback overhead as well as low implementation complexity, the dual-structured linear precoding scheme is adopted, which is based on the two timescale channel state information (CSI) and the dual-polarized antenna structure. The subgrouping technique, which is based on polarization, is also utilized to divide spatially grouped users into co-polarized subgroups to further reduce channel feedback overhead. The proposed robust system EE precoding design can achieve the maximization of the worst-case system EE, with the norm-bounded channel errors of all users. This robust EE optimization is naturally decomposed into two parts. In the first part, based on the polarized spatial correlation information, the block diagonalization is utilized to design the preprocessing matrix. In the second part, based on the relationship between the mean square error and the signal-to-interference-plus-noise ratio, the linear precoding matrix can be optimized by utilizing the sign-definiteness lemma and the fractional programming technique. Specifically, the corresponding nonconvex EE fractional optimization problem is converted to a series of semidefinite programming problems, which are solved by the convex optimization method efficiently. Simulation results indicate that the proposed two timescale based dual-structured precoding has many advantages on the robust system EE performance in the dual-polarized multiuser MIMO system.

Angle-based beamforming in mmWave massive MIMO systems with low feedback overhead using multi-pattern codebooks

The integration of millimeter-wave (mmWave) communications and massive multiple input multiple output (MIMO) techniques is a promising solution to dramatically increase the 5G network throughput. By using large antenna arrays, beamforming can be adopted to improve the 5G capacity by employing spatial domain resources. In a frequency division duplexing (FDD) based 5G mmWave MIMO system, beamforming operation requires timely downlink channel state information (CSI) feedback. However, the rapid channel variations caused by short wavelength of mmWave band, and the high-level feedback information required due to the large number of antennas in massive MIMO system lead to the significantly increased beamforming overhead. In this paper, by exploiting the higher angular stability of such channels, we propose an angle-based beamforming scheme to reduce the feedback frequency and the number of feedback bits. To facilitate this approach users are initially selected to reduce the intra-zone interference before beamforming. Besides, location related feedback, which is not affected by the number of antennas, is adopted to reduce overhead. The simulation results show that two proposed user selection algorithms can adapt to scenarios with diverse requirements, while the feedback overhead of proposed angle-based beamforming algorithm is sharply reduce compared with that of CSI-based beamforming algorithm.

On the Two-User MISO Interference Channel With Single-User Decoding: Impact of Imperfect CSIT and Channel Dimension Reduction

This paper examines the Rayleigh fading multiple-input single-output interference channel with single-user decoding and limited channel state information (CSI) feedback. Its contribution is twofold. First, the achievable rate-region with imperfect CSI at the transmitters due to channel quantization errors is analyzed for the two-user case. An analytically tractable inner bound on that region is derived, which provides insights into the problem. Similarly to the case of perfect CSI at the transmitters, it can be shown that beamforming constitutes an optimal strategy for achieving the boundary points of the inner bound. Second, we present a novel CSI feedback scheme that reduces the cross-link CSI feedback overhead, and enhances throughput for any rate-limited feedback scheme. This feedback reduction is crucial when control channels for sharing information between transmitters and unintended receivers are rate limited. A distinguishing feature of the proposed scheme is that feedback is taken into account already at the channel estimation stage. While maintaining a high array gain in the direct channel towards the intended user, the scheme induces an effective low-dimensional cross-link channel, which can be quantized more accurately than the full-dimensional channel. This eventually leads to enhanced performance while maintaining a low CSI feedback overhead. Finally, the proposed feedback scheme is extended to the case of $N>2$ users and shown to provide a significant reduction in CSI feedback overhead in a practically oriented setting.

Wireless Multicast of Virtual Reality Videos With MPEG-I Format

Deploying virtual reality (VR) streaming systems over wireless networks can provide an immersive environment for users without behavioral restrictions, and thus has drawn considerable attentions recently. MPEG-I as a new panorama video standard just targets such immersive multimedia applications. Although multiple VR delivery schemes have been proposed, MPEG-I has not been sufficiently researched, especially for multicast scenarios. Therefore, in this paper, we would like to design a multicast scheme to deliver 360 VR videos with MPEG-I format. Specifically, based on the prediction of users' viewports, we formulate an optimization problem of user grouping and bandwidth allocation to maximize user utilities. To solve the problem, we first propose a method which is composed of an optimal bandwidth allocation algorithm and a two-level hierarchical user grouping scheme. Furthermore, we consider the channel feedback overhead in multicast scenarios with a large number of users. Based on a reasonable assumption, we propose a simplified grouping method with low feedback overhead. Simulation results demonstrate the effectiveness of our proposed method, which yields similar performance compared to an exhausting search method when serving a large number of users with high SNRs.

Channel Access and Power Control for Mobile Crowdsourcing in Device‐to‐Device Underlaid Cellular Networks

With the access of a myriad of smart handheld devices in cellular networks, mobile crowdsourcing becomes increasingly popular, which can leverage omnipresent mobile devices to promote the complicated crowdsourcing tasks. Device‐to‐device (D2D) communication is highly desired in mobile crowdsourcing when cellular communications are costly. The D2D cellular network is more preferable for mobile crowdsourcing than conventional cellular network. Therefore, this paper addresses the channel access and power control problem in the D2D underlaid cellular networks. We propose a novel semidistributed network‐assisted power and a channel access control scheme for D2D user equipment (DUE) pieces. It can control the interference from DUE pieces to the cellular user accurately and has low information feedback overhead. For the proposed scheme, the stochastic geometry tool is employed and analytic expressions are derived for the coverage probabilities of both the cellular link and D2D links. We analyze the impact of key system parameters on the proposed scheme. The Pareto optimal access threshold maximizing the total area spectral efficiency is obtained. Unlike the existing works, the performances of the cellular link and D2D links are both considered. Simulation results show that the proposed method can improve the total area spectral efficiency significantly compared to existing schemes.

An efficient CSI feedback scheme for dual-polarized MIMO systems using layered Multi-paths Information

Massive MIMO is one of the enabling technologies for beyond 4G and 5G systems due to its ability to provide beamforming gain and reduce interference Dual-polarized antenna is widely adopted to accommodate a large number of antenna elements in limited space. However, current CSI(channel state information) feedback schemes developed in LTE for conventional MIMO systems are not efficient enough for massive MIMO systems since the overhead increases almost linearly with the number of antenna. Moreover, the codebook for massive MIMO will be huge and difficult to design with the LTE methodology. This paper proposes a novel CSI feedback scheme named layered Multi-paths Information based CSI Feedback (LMPIF), which can achieve higher spectrum efficiency for dual-polarized antenna system with low feedback overhead. The MIMO channel is decomposed into long term components (multipath directions and amplitudes) and short term components (multipath phases). The relationship between the two components and the optimal precoder is derived in closed form. To reduce the overhead, different granularities in feedback time have been applied for the long term components and short term components Link and system level simulation results prove that LMPIF can improve performance considerably with low CSI feedback overhead.

Cell Coverage Extension With Orthogonal Random Precoding for Massive MIMO Systems

In this paper, we investigate a coverage extension scheme based on orthogonal random precoding (ORP) for the downlink of massive multiple-input multiple-output systems. In this scheme, a precoding matrix consisting of orthogonal vectors is employed at the transmitter to enhance the maximum signal-to-interference-plus-noise ratio of the user. To analyze and optimize the ORP scheme in terms of cell coverage, we derive the analytical expressions of the downlink coverage probability for two receiver structures, namely, the single-antenna receiver and multiple-antenna receiver with antenna selection. The simulation results show that the analytical expressions accurately capture the coverage behaviors of the systems employing the ORP scheme. It is also shown that the optimal coverage performance is achieved when a single precoding vector is used under the condition that the threshold of the signal-to-noise ratio of the coverage is greater than one. The performance of the ORP scheme is further analyzed when the different random precoder groups are utilized over multiple time slots to exploit precoding diversity. The numerical results show that the proposed ORP scheme over multiple time slots provides a substantial coverage gain over the space–time coding scheme despite its low feedback overhead.

Outage Performance of Selective Dual-Hop MIMO Relaying with OSTBC and Transmit Antenna Selection in Rayleigh Fading Channels

For dual-hop multiple-input multiple-output (MIMO) decode-and-forward relaying systems, we propose a selective relaying scheme that uses orthogonal space-time block code (OSTBC) and transmit antenna selection with maximal-ratio combining (TAS/MRC) or vice versa at the first and second hops, respectively. The aim is to achieve an asymptotically identical performance to the dual-hop relaying system with only TAS/MRC, while requiring lower feedback overhead. In particular, we give the selection criteria based on the antenna configurations and the average channel powers for the first and second hops, assuming Rayleigh fading channels. Also, the numerical results are shown for the outage performance comparison between the dual-hop DF relaying systems with the proposed scheme, only TAS/MRC, and only OSTBC.

RAMCAST: Reliable and Adaptive Multicast over IEEE 802.11n WLANs

Wireless multicast over IEEE 802.11 WLANs suffers from two well-known problems: poor reliability and low spectral efficiency. To overcome these problems, we propose a novel PHY/MAC cross-layer wireless multicast scheme called reliable and adaptive multicast (RAMCAST). By considering the frame aggregation of IEEE 802.11n, RAMCAST enables an access point (AP) to selectively retransmit erroneous multicast frames and to dynamically adjust modulation and coding scheme under varying channel conditions. In particular, empowered by the orthogonality of subcarriers in the OFDM symbol, RAMCAST enables multiple multicast clients to transmit feedback to the AP simultaneously without collision, resulting in very low feedback overhead. We verified the feasibility of RAMCAST through USRP/GNU radio-based experiments and conducted an extensive simulation study using ns-2, and we found that RAMCAST outperforms the state-of-the-art wireless multicast scheme.

Trellis-Extended Codebooks and Successive Phase Adjustment: A Path From LTE-Advanced to FDD Massive MIMO Systems

It is of great interest to develop efficient ways to acquire accurate channel state information (CSI) for frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems for backward compatibility. It is theoretically well known that the codebook size for CSI quantization should be increased as the number of transmit antennas becomes larger, and 3GPP long term evolution (LTE) and LTE-Advanced codebooks also follow this trend. Thus, in massive MIMO, it is hard to apply the conventional approach of using pre-defined vector-quantized codebooks for CSI quantization mainly because of codeword search complexity. In this paper, we propose a trellis-extended codebook (TEC) that can be easily harmonized with current wireless standards such as LTE or LTE-Advanced by extending standardized codebooks designed for 2, 4, or 8 antennas with trellis structures. TEC exploits a Viterbi decoder and convolutional encoder in channel coding as the CSI quantizer and the CSI reconstructer, respectively. By quantizing multiple channel entries simultaneously using standardized codebooks in a state transition of trellis search, TEC can achieve fractional bits per channel entry quantization to have a practical feedback overhead. Thus, TEC can solve both the complexity and the feedback overhead issues of CSI quantization in massive MIMO systems. We also develop trellis-extended successive phase adjustment (TE-SPA) which works as a differential codebook of TEC. This is similar to the dual codebook concept of LTE-Advanced. TE-SPA can reduce CSI quantization error even with lower feedback overhead in temporally correlated channels. Numerical results verify the effectiveness of the proposed schemes in FDD massive MIMO systems.

Constant-Delay and Constant-Feedback Moving Window Network Coding for Wireless Multicast: Design and Asymptotic Analysis

A major challenge of wireless multicast is to be able to support a large number of users while simultaneously maintaining low delay and low feedback overhead. In this paper, we develop a joint coding and feedback scheme named Moving Window Network Coding with Anonymous Feedback (MWNC-AF) that successfully addresses this challenge. In particular, we show that our scheme simultaneously achieves both a constant decoding delay and a constant feedback overhead, irrespective of the number of receivers $n$, without sacrificing either throughput or reliability. We explicitly characterize the asymptotic decay rate of the tail of the delay distribution, and prove that transmitting a fixed amount of information bits into the MWNC-AF encoder buffer in each time-slot (called "constant data injection process") achieves the fastest decay rate, thus showing how to obtain delay optimality in a large deviation sense. We then investigate the average decoding delay of MWNC-AF, and show that when the traffic load approaches the capacity, the average decoding delay under the constant injection process is at most one half of that under a Bernoulli injection process. In addition, we prove that the per-packet encoding and decoding complexity of MWNC-AF both scale as $O(\log n)$, with the number of receivers $n$. Our simulations further underscore the performance of our scheme through comparisons with other schemes and show that the delay, encoding and decoding complexity are low even for a large number of receivers, demonstrating the efficiency, scalability, and ease of implementability of MWNC-AF.

Bit error probability of decode‐and‐forward relaying with efficient partial relay selection in non‐identical Rayleigh fading channels

Efficient partial relay selection (EPRS) is an advanced technique to improve the performance of partial relay selection (PRS) at the cost of a small additional feedback overhead. However, EPRS has the worst performance but lower feedback overhead when compared with best relay selection. In this study, the authors present a bit error probability (BEP) analysis of EPRS in decode-and-forward relaying systems over independent and non-identical Rayleigh fading channels, where the direct link between the source and the destination is available. In particular, they provide an exact and closed-form expression of the BEP of M-ary square quadrature amplitude modulation for EPRS. The BEP analysis is verified through simulations. The numerical results show that EPRS significantly outperforms PRS for a large gap between the average channel powers for the first and the second hops except when all the average channel powers for the first hop are smaller than those for the second hop.

Noncoherent Trellis Coded Quantization: A Practical Limited Feedback Technique for Massive MIMO Systems

Accurate channel state information (CSI) is essential for attaining beamforming gains in single-user (SU) multiple-input multiple-output (MIMO) and multiplexing gains in multi-user (MU) MIMO wireless communication systems. State-of-the-art limited feedback schemes, which rely on pre-defined codebooks for channel quantization, are only appropriate for a small number of transmit antennas and low feedback overhead. In order to scale informed transmitter schemes to emerging massive MIMO systems with a large number of transmit antennas at the base station, one common approach is to employ time division duplexing (TDD) and to exploit the implicit feedback obtained from channel reciprocity. However, most existing cellular deployments are based on frequency division duplexing (FDD), hence it is of great interest to explore backwards compatible massive MIMO upgrades of such systems. For a fixed feedback rate per antenna, the number of codewords for quantizing the channel grows exponentially with the number of antennas, hence generating feedback based on look-up from a standard vector quantized codebook does not scale. In this paper, we propose noncoherent trellis-coded quantization (NTCQ), whose encoding complexity scales linearly with the number of antennas. The approach exploits the duality between source encoding in a Grassmannian manifold (for finding a vector in the codebook which maximizes beamforming gain) and noncoherent sequence detection (for maximum likelihood decoding subject to uncertainty in the channel gain). Furthermore, since noncoherent detection can be realized near-optimally using a bank of coherent detectors, we obtain a low-complexity implementation of NTCQ encoding using an off-the-shelf Viterbi algorithm applied to standard trellis coded quantization. We also develop advanced NTCQ schemes which utilize various channel properties such as temporal/spatial correlations. Monte Carlo simulation results show the proposed NTCQ and its extensions can achieve near-optimal performance with moderate complexity and feedback overhead.