The Impact of Channel Feedback on Opportunistic Relay Selection for Hybrid-ARQ in Wireless Networks

This paper presents a decentralized relay selection protocol for a dense wireless network and describes channel feedback strategies that improve its performance. The proposed selection protocol supports hybrid automatic-repeat-request transmission where relays forward parity information to the destination in the event of a decoding error. Channel feedback is employed for refining the relay selection process and for selecting an appropriate transmission mode in a proposed adaptive modulation transmission framework. An approximation of the throughput of the proposed adaptive modulation strategy is presented, and the dependence of the throughput on system parameters such as the relay contention probability and the adaptive modulation switching point is illustrated via maximization of this approximation. Simulations show that the throughput of the proposed selection strategy is comparable to that yielded by a centralized selection approach that relies on geographic information.Comment: 30 pages, 9 figures, submitted to the IEEE Transactions on Vehicular Technology, revised March 200

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

Adaptive Turbo-Coded Hybrid-ARQ in OFDM Systems over Gaussian and Fading Channels

In this paper, an analytical approach for spectral efficiency maximization of coded wideband transmissions is presented based on OFDM. The approach exploits Type-III Hybrid-ARQ, enabling all sub-carriers to be employed in codeword transmission regardless of the sub-carrier conditions. The effects of imperfect sub-channel estimation are characterized and compensated for during code rate and signal constellation optimization. The results of the paper highlight that by independently adapting the code rate and signal constellation to individual OFDM sub-carriers based on an estimated sub-carrier CSI, the overall spectral efficiency of the system is maximized

Cross-layer link adaptation for goodput optimization in MIMO BIC-OFDM systems

This work proposes a novel cross-layer link performance prediction (LPP) model and link adaptation (LA) strategy for soft-decoded multiple-input multiple-output (MIMO) bit-interleaved coded orthogonal frequency division multiplexing (BIC-OFDM) systems employing hybrid automatic repeat request (HARQ) protocols. The derived LPP, exploiting the concept of effective signal-to-noise ratio mapping (ESM) to model system performance over frequency-selective channels, does not only account for the actual channel state information at the transmitter and the adoption of practical modulation and coding schemes (MCSs), but also for the effect of the HARQ mechanism with bit-level combining at the receiver. Such method, named aggregated ESM, or αESM for short, exhibits an accurate performance prediction combined with a closed-form solution, enabling a flexible LA strategy, that selects at every protocol round the MCS maximizing the expected goodput (EGP), i.e., the number of correctly received bits per unit of time. The analytical expression of the EGP is derived capitalizing on the αESM and resorting to the renewal theory. Simulation results carried out in realistic wireless scenarios corroborate our theoretical claims and show the performance gain obtained by the proposed αESM-based LA strategy when compared with the best LA algorithms proposed so far for the same kind of systems