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The optimum designs of linear multihop networks that can minimize the end-to-end transmission delays are studied in this paper. In multihop networks, more hops mean a shorter transmission distance per hop but more overheads; thus, it is critical to identify the optimum number of hops that can minimize the end-to-end delay. Two network configurations are considered: one with deterministic equidistant relays and the other with random relays uniformly distributed between the source and destination. The average end-to-end delays of both networks operating in the presence of noise and/or interference are expressed as functions of a number of system parameters, such as channel propagations, noise, interference, protocol overhead, and the geometric distributions of the relays. Based on the analytical results, the optimum number of hops for various system configurations is obtained. It is shown that networks with equidistant relays can achieve a shorter end-to-end delay than those with uniformly distributed relays.

This paper discusses the energy- and spectral-efficient transmissions for delay-constrained wireless communication systems utilizing hybrid automatic repeat request (HARQ). Three design metrics are considered: 1) the energy efficiency (EE) measured by the average energy required to successfully deliver one information bit from a source to its destination; 2) the spectral efficiency (SE) defined as the average data rate per unit bandwidth; and 3) the average energy per bit normalized by the SE. Optimum system designs with respect to different metrics are developed by analytically identifying the sequence of transmission energy that should be employed at different retransmissions. The optimum energy distributions are calculated with a new backward sequential calculation method, where the energy at each retransmission round is expressed as a closed-form expression of a wide range of practical system parameters, such as circuit power and channel coding in the physical layer and frame length and protocol overhead in the media access control layer. Reducing the SE-normalized energy per bit yields a balanced tradeoff between EE and SE. Numerical results demonstrate that reducing the SE-normalized energy per bit achieves a 26.7% SE gain over the system that minimizes the average energy per bit; yet, the EE of the two systems is almost identical.

In this paper, a low-complexity detection scheme is proposed for an underdetermined multiple-input-multiple-output (UD-MIMO) wireless communication system that employs N transmit antennas and M< Nreceive antennas. The proposed scheme combines a simplified parallel interference cancelation (S-PIC) with the block decision feedback equalization (BDFE) algorithm. To account for the extra (N − M )-dimension in the transmitted signal, the UD-MIMO system is partitioned into two subsystems: one with (N − M ) transmit antennas and the other one with M transmit antennas. The interference from the first subsystem to the second one is canceled in parallel, and BDFE is performed over the second subsystem. Unlike conventional PIC methods that exhaustively search all the Q (N −M ) sequences in the first subsystem, with Q being the constellation size, the proposed scheme explores only a small number of candidate sequences in the first subsystem; thus, it achieves significant complexity reduction. Two new candidate sequence selection methods are proposed. In the first iteration, the candidate sequences used for PIC are selected by exploring the statistical properties of the received signals. In the second iteration and beyond, the set containing the candidate sequences is constructed by utilizing the soft informa- tion generated from the previous iteration. The proposed scheme provides a balanced tradeoff between computational complexity and bit error rate (BER) performance. Index Terms—Block decision feedback equalization (BDFE), parallel interference cancelation (PIC), turbo detection, under- determined multiple-input multiple-output (UD-MIMO), wireless communication.

The joint estimation of carrier frequency offset (CFO) and channel transfer function (CTF) for orthogonal frequency-division multiplexing (OFDM) systems with phase noise is discussed in this paper. A CFO estimation algorithm is developed by exploring the time-frequency structure of specially designed training symbols, and it provides a very accurate estimation of the CFO in the presence of both unknown frequency-selective fading and phase noise. Based on the estimated CFO, phase noise and frequency-selective fading are jointly estimated by employing the maximum a posteriori (MAP) criterion. Specifically, the fading channel is estimated in the form of the frequency-domain CTF. The estimation of the CTF eliminates the requirement of a priori knowledge of channel length, and it is simpler compared with the time-domain channel impulse response (CIR) estimation methods used in the literature. Theoretical analysis with the Cramer-Rao lower bound (CRLB) demonstrates that the proposed CFO and CTF estimation algorithms can achieve near-optimum performance.

Theoretical error performances of wireless communication systems suffering from both doubly selective (time varying and frequency selective) Rayleigh fading and sampler timing offset are analyzed in this paper. Single-input-single-output systems with doubly selective fading channels are equivalently represented as discrete-time single-input-multiple-output (SIMO) systems with correlated frequency-flat fading channels, with the correlation information being determined by the combined effects of sampler timing phase, maximum Doppler spread, and power delay profile of the physical fading. Based on the equivalent SIMO system representation, closed-form error-probability expressions are derived as tight lower bounds for linearly modulated systems with fractionally spaced equalizers. The information on the sampler timing offset and the statistical properties of the physical channel fading, along with the effects of the fractionally spaced equalizer, are incorporated in the error-probability expressions. Simulation results show that the new analytical results can accurately predict the error performances of maximum-likelihood sequence estimation and maximum a posteriori equalizers for practical wireless communication systems in a wide range of signal-to-noise ratio. Moreover, some interesting observations about receiver oversampling and system timing phase sensitivity are obtained based on the new analytical results

In this paper, a novel channel-estimation scheme for an 8-PSK enhanced data rates for GSM evolution (EDGE) system with fast time-varying and frequency-selective fading channels is presented. Via a mathematical derivation and simulation results, the channel impulse response (CIR) of the fast fading channel is modeled as a linear function of time during a radio burst in the EDGE system. Therefore, a least-squares-based method is proposed along with the modified burst structure for time-varying channel estimation. Given that the pilot-symbol blocks are located at the front and the end of the data block, the LS-based method is able to estimate the parameters of the time-varying CIR accurately using a linear interpolation. The proposed time-varying estimation algorithm does not cause an error floor that existed in the adaptive algorithms due to a nonideal channel tracking. Besides, the time-varying CIR in the EDGE system is not in its minimum-phase form, as is required for low-complexity reduced-state equalization methods. In order to maintain a good system performance, a Cholesky-decomposition method is introduced in front of the reduced-state equalizer to transform the time-varying CIR into its minimum-phase equivalent form. Via simulation results, it is shown that the proposed algorithm is very well suited for the time-varying channel estimation and equalization, and a good bit-error-rate performance is achieved even at high Doppler frequencies up to 300 Hz with a low complexity