We investigate the primitive diamond relay channel model comprising Gaussian channels with identical frequency responses from the user to the relays and with lossless fronthaul links with a limited rate from the relays to the destination. The model is further extended by addressing correlated noise at the relays, which can be present in the uplink system, for example, due to interference or a jammer. We use the oblivious compress and forward (CF) scheme with distributed compression, and the decode and forward (DF) scheme. The CF system rate is calculated for the correlated noise case and a closed-form formula is derived. The effect of positive and negative correlation on the system rate is shown. It is proved that CF-DF time-sharing scheme is advantageous over a CF-DF superposition coding (SPC) scheme for the correlated noise case. We also analyze another scheme to combine CF and DF, which is based on dirty paper coding (DPC). This scheme’s analysis relies on the correlated noise CF results, providing another motivation for examining this case. It is proved that also in this setting, the CF-DF time-sharing scheme is advantageous over the CF-DF DPC scheme. The optimal time-sharing proportion between CF and DF, and each frequency’s power and rate allocations are determined for positive noise correlation.

We investigate a special case of diamond relay comprising Gaussian channels with an identical frequency response from the user to the relays, and with lossless fronthaul links with limited rate from the relays to the destination. We use the oblivious compress and forward (CF) scheme with with distributed compression, and a decode and forward (DF) scheme, where each relay decodes the whole message and sends half of the bits to the destination. It is proved that optimal CF-DF time-sharing scheme is advantageous over the CF-DF superposition scheme. We derive an achievable rate by using time-sharing between CF and DF. The optimal time-sharing proportion between CF and DF, and the power and rate allocations are different for each frequency and are fully determined.

Consider a primitive diamond relay channel, where a source X wants to send information to a destination with the help of two relays Y1and Y2, and the two relays can communicate to the destination via error-free digital links of capacities C1and C2respectively, while Y1and Y2are conditionally independent given X. In this paper, we develop new upper bounds on the capacity of such primitive diamond relay channels that are tighter than the cut-set bound. Our results include both the Gaussian and the discrete memoryless case and build on the information inequalities recently developed in [6]-[8] that characterize the tension between information measures in a certain Markov chain.

We consider systems in which the transmitter conveys messages to the receiver through a capacity-limited relay station. The channel between the transmitter and the relay station is assumed to be a frequency-selective additive Gaussian noise channel. It is assumed that the transmitter can shape the spectrum and adapt the coding technique so as to optimize performance. The relay operation is oblivious (nomadic transmitters), that is, the specific codebooks used are unknown. We find the reliable information rate that can be achieved with Gaussian signaling in this setting, and to that end, employ Gaussian bottleneck results combined with Shannon's incremental frequency approach. We also prove that, unlike classical water pouring, the allocated spectrum (power and bit rate) of the optimal solution could frequently be discontinuous. These results can be applied also to a MIMO transmission scheme. We also investigate the case of an entropy-limited relay. We show that the optimal relay function is always deterministic, present lower and upper bounds on the optimal performance (in terms of mutual information), and derive an analytical approximation.

In this paper we investigate the achievable rate of a system that includes a nomadic transmitter with several antennas, which is received by multiple agents, each with a single antenna, suffering independent channel coefficients and additive Gaussian noises. Since the transmitter is nomadic, the agents do not have any decoding ability. These agents process their channel observations and forward it to the final destination through lossless links with a fixed given capacity. Assuming Gaussian signalling, we get lower and upper bounds on the achievable rates, and demonstrate the achievability of the full multiplexing gain. We also extend the model to address multi-user systems. The asymptotic setting with numbers of agents and transmitter's antennas taken to infinity is examined, and the incompetence of the simple compression when compared to a Wyner-Ziv scheme is demonstrated. For finite setting, an upper-bound is derived, which turns out to be quite tight when compared to the Wyner-Ziv achievable rate, even for a rather small 4 × 4 system.

An efficient scheme for the multiple-access multiple-input multiple-output (MIMO) channel is proposed, which operates well also in the single user regime, as well as in a direct-sequence spread-spectrum (DS-CDMA) setting. The design features scalability and is of limited complexity. The system employs optimized low-density parity-check (LDPC) codes and an efficient iterative (belief propagation-BP) detection which combines linear minimum mean-square error (LMMSE) detection and iterative interference cancellation (IC). This combination is found to be necessary for efficient operation in high system loads /spl alpha/>1. An asymptotic density evolution (DE) is used to optimize the degree polynomials of the underlining LDPC code, and thresholds as close as 0.77 dB to the channel capacity are evident for a system load of 2. Replacing the LMMSE with the complex individually optimal multiuser detector (IO-MUD) further improves the performance up to 0.14 dB from the capacity. Comparing the thresholds of a good single-user LDPC code to the multiuser optimized LDPC code, both over the above multiuser channel, reveals a surprising 8-dB difference, emphasizing thus the necessity of optimizing the code. The asymptotic analysis of the proposed scheme is verified by simulations of finite systems, which reveal meaningful differences between the performances of MIMO systems with single and multiple users and demonstrate performance similar to previously reported techniques, but with higher system loads, and significantly lower receiver complexity.

Standard VLSI implementations of turbo decoding require substantial memory and incur a long latency, which cannot be tolerated in some applications. A parallel VLSI architecture for low-latency turbo decoding, comprising multiple single-input single-output (SISO) elements, operating jointly on one turbo-coded block, is presented and compared to sequential architectures. A parallel interleaver is essential to process multiple concurrent SISO outputs. A novel parallel interleaver and an algorithm for its design are presented, achieving the same error correction performance as the standard architecture. Latency is reduced up to 20 times and throughput for large blocks is increased up to six-fold relative to sequential decoders, using the same silicon area, and achieving a very high coding gain. The parallel architecture scales favorably: latency and throughput are improved with increased block size and chip area.

A new suboptimal demodulator based on a singular value decomposition for estimation of unitary matrices is introduced. Noncoherent communication over the Rayleigh flat fading channel with multiple transmit and receive antennas, where no channel state information is available at the receiver is investigated. Codes achieving bit-error rate (BER) lower than 10/sup -4/ at bit energy over the noise spectral density ratio (E/sub b//N/sub 0/) of 1.6-1.9 dB from code restricted capacity limit were found. At higher data rates, computation of code restricted capacity is impractical. Therefore, the mutual information upper bound of the capacity attaining isotropically random unitary transmit matrices was used. The codes achieve BER lower than 10/sup -4/ at E/sub b//N/sub 0/ of 3.2-6 dB from this bound, with coding rates of 1.125-5.06 bits per channel use, and different modulation decoding complexities. The codes comprise a serial concatenation of turbo code and a unitary matrix differential modulation code. The receiver employs the high-performance coupled iterative decoding of the turbo code and the modulation code. Information theoretic arguments are harnessed to form guidelines for code design and to evaluate performance of the iterative decoder.

A new suboptimal demodulator based on iterative decision feedback demodulation (DFD), and a singular value decomposition (SVD) for estimation of unitary matrices, is introduced. Noncoherent communication over the Rayleigh flat-fading channel with multiple transmit and receive antennas, where no channel state information (CSI) is available at the receiver is investigated. With four transmit antennas, codes achieving bit-error rate (BER) lower than 10/sup -4/ at bit energy over the noise spectral density ratio (E/sub b//N/sub o/) of -0.25 dB up to 3.5 dB, with coding rates of 1.6875 to 5.06 bits per channel use were found. The performance is compared to the mutual information upper bound of the capacity attaining isotropically random (IR) unitary transmit matrices. The codes achieve BER lower than 10/sup -4/ at E/sub b//N/sub o/ of 3.2 dB to 5.8 dB from this bound. System performance including the iterative DFD algorithm is compared to the one using Euclidean distance, as a reliability measure for demodulation . The DFD system presents a performance gain of up to 1.5 dB. Uncoded systems doing iterative DFD demodulation and idealized pilot sequence assisted modulation (PSAM) detection are compared. Iterative DFD introduces a gain of more than 1.2 dB. The coded system comprises a serial concatenation of turbo code and a unitary matrix differential modulation code. The receiver employs the high-performance coupled iterative decoding of the turbo code and the modulation code. Information-theoretic arguments are harnessed to form guidelines for code design and to evaluate performance of the iterative decoder.

A new sub-optimal demodulator based on a singular value decomposition (SVD) for estimation of unitary matrices is introduced for non-coherent communication over the Rayleigh flat fading channel with multiple transmit and receive antennas, where no channel state information (CSI) is available. Codes achieving bit error rate lower than 10/sup -4/ at bit energy over the noise spectral density ratio (E/sub b//N/sub 0/) of 1.7 dB from code restricted capacity limit or of 3.2 dB and higher from a mutual information upper bound of the capacity attaining isotropically random unitary transmit matrices, were found with coding rates of 1.125 to 5.06 bits per channel use, and different modulation decoding complexities. The codes comprise a serial concatenation of turbo code and a unitary matrix differential modulation code. The receiver employs the high performance joint iterative decoding of the turbo code and the modulation code.

Turbo codes achieve performance near the Shannon limit. Standard sequential VLSI implementation of turbo decoding requires large memory and incurs a long latency, which cannot be tolerated in some applications. A novel parallel VLSI architecture for turbo decoding is described, comprising multiple SISO (soft-in soft-out) elements, operating jointly on one turbo coded block, and a new parallel interleaver. Latency is reduced up to twenty times and throughput for large blocks is increased up to five-fold relative to sequential decoders, using the same area of silicon, and achieving the same coding gain. The parallel architecture scales favourably - latency and throughput improve with growing block size and chip area.

We study a serially interleaved concatenated code construction, where the outer code is a standard convolutional code, and the inner code is a recursive convolutional code of rate 1. We focus on the ubiquitous inner differential encoder (used, in particular, to resolve phase ambiguities), double differential encoder (used to resolve both phase and frequency ambiguities), and another rate 1 recursive convolutional code of memory 2. We substantiate analytically the rather surprising result, that the error probabilities corresponding to a maximum-likelihood (ML) coherently detected antipodal modulation over the additive white Gaussian noise (AWGN) channel for this construction are advantageous as compared to the stand-alone outer convolutional code. This is in spite of the fact that the inner code is of rate 1. The analysis is based on the tangential sphere upper bound of an ML decoder, incorporating the ensemble weight distribution (WD) of the concatenated code, where the ensemble is generated by all random and uniform interleavers. This surprising result is attributed to the WD thinning observed for the concatenated scheme which shapes the WD of the outer convolutional code to resemble more closely the binomial distribution (typical of a fully random code of the same length and rate). This gain is maintained regardless of a rather dramatic decrease, as demonstrated here, in the minimum distance of the concatenated scheme as compared to the minimum distance of the outer stand-alone convolutional code. The advantage of the examined serially interleaved concatenated code, given in terms of bit and/or block error probability which is decoded by a practical suboptimal decoder, over the optimally decoded standard convolutional code is demonstrated by simulations, and some insights into the performance of the iterative decoding algorithm are also discussed. Though we have investigated only specific constructions of constituent inner (rate 1) and outer codes, we trust, hinging on the rational of the arguments here, that these results extend to many other constituent convolutional outer codes and rate 1 inner recursive convolutional codes.

The capacity of M-ary phase-shift keying (MPSK) over an additive white Gaussian noise (AWGN) channel with carrier phase unknown but constant over L symbols is investigated. It is shown that capacity-achieving channel inputs are uniformly distributed and independent MPSK symbols. Capacity over a range of signal-to-noise ratio (SNR) and L is presented for binary phase-shift keying (BPSK) and quaternary phase-shift keying (QPSK). Upper and lower easy-to-compute bounds on capacity are derived. It is proven that for large L the coherent capacity is approached. An analytic asymptotic expression for low L/spl middot/SNR is derived exhibiting the expected quadratic dependence on the SNR.