Using Channel Output Feedback to Increase Throughput in Hybrid-ARQ

Hybrid-ARQ protocols have become common in many packet transmission systems due to their incorporation in various standards. Hybrid-ARQ combines the normal automatic repeat request (ARQ) method with error correction codes to increase reliability and throughput. In this paper, we look at improving upon this performance using feedback information from the receiver, in particular, using a powerful forward error correction (FEC) code in conjunction with a proposed linear feedback code for the Rayleigh block fading channels. The new hybrid-ARQ scheme is initially developed for full received packet feedback in a point-to-point link. It is then extended to various different multiple-antenna scenarios (MISO/MIMO) with varying amounts of packet feedback information. Simulations illustrate gains in throughput.Comment: 30 page

Relay Switching Aided Turbo Coded Hybrid-ARQ for Correlated Fading Channel

Hybrid-Automatic-Repeat-reQuest (HARQ) has become an indispensable technique in reliable communications systems. However, its performance is inevitably affected by the channel’s fading correlation. In this paper, we proposed a novel relay-switching aided HARQ scheme in order to mitigate the detrimental effects of correlated fading without unduly increasing the system’s complexity and delay. Our results show that the proposed relay-switching regime operates efficiently in correlated channels, hence significantly reduces the error floor of turbo-coded HARQ. Additionally, a HARQ scheme using Segment Selective Repeat (SSR) is incorporated in the relay-switching scheme for achieving further improvements. Quantitatively, the proposed relay-switching aided turbo-coded HARQ scheme using SSR may achieve an approximately 2 dB gain, compared to the conventional amplify-and-forward aided turbo coded HARQ arrangement using Chase Combining. Index Terms - Relay switching, correlated fading channel, Hybrid-ARQ, turbo codes, chase combining, incremental redundancy, selective segment repeat

Multi-level Turbo Decoding Assisted Soft Combining Aided Hybrid ARQ

Hybrid Automatic Repeat reQuest (ARQ) plays an essential role in error control. Combining the incorrectly received packet replicas in hybrid ARQ has been shown to reduce the resultant error probability, while improving the achievable throughput. Hence, in this contribution, multi-level turbo codes have been amalgamated both with hybrid ARQ and efficient soft combining techniques for taking into account the Log- Likelihood Ratios (LLRs) of retransmitted packet replicas. In this paper, we present a soft combining aided hybrid ARQ scheme based on multi-level turbo codes, which avoid the capacity loss of the twin-level turbo codes that are typically employed in hybrid ARQ schemes. More specifically, the proposed receiver dynamically appends an additional parallel concatenated Bahl, Cocke, Jelinek and Raviv (BCJR) algorithm based decoder in order to fully exploit each retransmission, thereby forming a multi-level turbo decoder. Therefore, all the extrinsic information acquired during the previous BCJR operations will be used as a priori information by the additional BCJR decoders, whilst their soft output iteratively enhances the a posteriori information generated by the previous decoding stages. We also present link- level Packet Loss Ratio (PLR) and throughput results, which demonstrate that our scheme outperforms some of the previously proposed benchmarks

Energy Optimization for Hybrid ARQ

Hybrid automatic repeat request (HARQ) \cite{costello1983error} plays an important role in providing reliable and efficient data transmission. In wireless communications, the wireless channel may vary fast, due to the mobility of the transmitter/receiver and the channel. Forward error correction (FEC) and automatic repeat request (ARQ) are two basic techniques to control errors. FEC employs error correction coding, by adding parity bits to the information bits, to combat channel errors. ARQ allows the receiver to request a retransmission of the packet when an error is detected in the received packet. HARQ gives protection to the wireless transmission by combining FEC and ARQ. In typical HARQ systems, redundancy is added to the information bits, and a retransmission is performed until either the packet is successfully decoded, or a maximum number of transmissions is reached.The motivation to optimize the energy consumption of HARQ is the high energy consumption of wireless communications on mobile devices. Wireless devices usually have a limited battery life, and wireless communications consume the majority of the battery energy of mobile devices. One example is that 3G and Wifi units consume more than 50\% of the energy for some smart phones \cite{tawalbeh2016studying}. Another example is that battery depletion has been identified as one of the primary factors that limit the lifetime of wireless sensor networks \cite{verdone2010wireless}.Previous works on HARQ mainly use information-theoretic approach, which assumes that the number of bits in each transmission round is sufficiently large. This assumption does not necessarily hold for actual codes with finite length. Therefore, in this dissertation, we consider HARQ with actual codes. We use turbo-coded HARQ, since turbo codes are well-known capacity-approaching codes \cite{berrou1993near} and widely used in standards such as 3GPP Long-Term Evolution (LTE) \cite{3gpp2007mulltiplexing}. We study the energy optimization for HARQ in two scenarios: the energy optimization for incremental redundancy (IR) HARQ, and the energy optimization for HARQ in wireless video transmission. For IR HARQ, each retransmission contains additional parity bits beyond those of the previous transmissions. For the first scenario, we consider different cases of channel state information (CSI) at the transmitter: the transmitter has no knowledge of any CSI, or knows the CSI in previous transmission rounds through a perfect feedback channel, or knows both current and previous CSI. The transmitter decides the forward error correction code rate based on the CSI it has. We minimize the energy consumption of turbo-coded HARQ, subject to a packet loss rate constraint. Numerical results show that the energy consumption of HARQ decreases when more CSI information is available at the transmitter. We also compare IR combining with both Chase combining and the system without combining, and IR combining yields the least energy consumption.For the second scenario, we formulate the problem as maximizing the video quality, subject to a constraint on the wireless transmission energy consumption. We consider multiple parameters in multiple layers in a wireless video transmission system: transmit power, alphabet size, FEC code rate, maximum number of transmissions and unequal video data importance. An analytical framework is proposed to include these parameters, which allows us to divide this problem into two sub-problems: data transmission and unequal error protection (UEP) for video content. The problem is tackled by solving the two sub-problems, which are done by exhaustive search and convex optimization, respectively. Simulations of different videos show that the proposed scheme outperforms methods using conventional data transmission and/or unequal error protection. For example, in the low SNR region, there is a total gain of 4.8 to 5.6dB on the peak signal-to-noise ratio of the received video compared to video transmission using conventional HARQ without any video UEP

Rateless Coding for Gaussian Channels

A rateless code-i.e., a rate-compatible family of codes-has the property that codewords of the higher rate codes are prefixes of those of the lower rate ones. A perfect family of such codes is one in which each of the codes in the family is capacity-achieving. We show by construction that perfect rateless codes with low-complexity decoding algorithms exist for additive white Gaussian noise channels. Our construction involves the use of layered encoding and successive decoding, together with repetition using time-varying layer weights. As an illustration of our framework, we design a practical three-rate code family. We further construct rich sets of near-perfect rateless codes within our architecture that require either significantly fewer layers or lower complexity than their perfect counterparts. Variations of the basic construction are also developed, including one for time-varying channels in which there is no a priori stochastic model.Comment: 18 page