Massive MIMO uses a large number of antennas to increase the spectral efficiency (SE) through spatial multiplexing of users, which requires accurate channel state information. It is often assumed that regular pilots (RP), where a fraction of the time-frequency resources is reserved for pilots, suffices to provide high SE. However, the SE is limited by the pilot overhead and pilot contamination. An alternative is superimposed pilots (SP) where all resources are used for pilots and data. This removes the pilot overhead and reduces pilot contamination by using longer pilots. However, SP suffers from data interference that reduces the SE gains. This paper proposes the Massive-MIMO Iterative Channel Estimation and Decoding (MICED) algorithm where partially decoded data is used as side-information to improve the channel estimation and increase SE. We show that users with precise data estimates can help users with poor data estimates to decode. Numerical results with QPSK modulation and LDPC codes show that the MICED algorithm increases the SE and reduces the block-error-rate with RP and SP compared to conventional methods. The MICED algorithm with SP delivers the highest SE and it is especially effective in scenarios with short coherence blocks like high mobility or high frequencies.

We establish a multiuser extrinsic information transfer (EXIT) chart area theorem for the interleave-division multiple access (IDMA) scheme, a special form of superposition coding, in multiple access channels (MACs). A low-cost multi-user detection (MUD) based on the Gaussian approximation (GA) is assumed. The evolution of mean-square errors (MSE) of the GA-based MUD during iterative processing is studied. We show that the K-dimensional tuples formed by the MSEs of K users constitute a conservative vector field. The achievable rate is a potential function of this conservative field, so it is the integral along any path in the field with value of the achievable rate solely determined by the two path terminals. Optimized error correcting codes can be found given the integration paths in the MSE fields by matching EXIT type functions. The above findings imply that i) low-cost GA detection can provide MAC capacity-approaching performance, ii) the sum-rate capacity can be achieved independently of the integration path in the MSE fields; and iii) the integration path determining achievable rate tuples of all users can be an extra degree of freedom for code design.

We establish a multi-user extrinsic information transfer (EXIT) chart area theorem for the interleave-division multiple-access (IDMA) scheme, a special form of superposition coding, in multiple access channels (MACs). A low-cost multi-user detection (MUD) based on the Gaussian approximation (GA) is assumed. The evolution of mean-square errors (MSE) of the GA-based MUD during iterative processing is studied. We show that the K-dimensional tuples formed by the MSEs of K users constitute a conservative vector field. The achievable rate is a potential function of this conservative field, so it is the integral along any path in the field with value of the integral solely determined by the two path terminals. Optimized codes can be found given the integration paths in the MSE fields by matching EXIT type functions. The above findings imply that i) low-cost GA-based MUD can provide near capacity performance; ii) the sum-rate capacity (region) can be achieved independently of the integration path in the MSE fields; and iii) the integration path can be an extra degree of freedom for code design.

This paper considers the forward error correction (FEC) code design for approaching the capacity of adynamicmultiple access channel (MAC) where both the number of users and their respective signal powers keep constantly changing, resembling the scenario of an actual wireless cellular system. To obtain a low-complexity non-orthogonal multiple access (NOMA) scheme, we propose a serial concatenation of a low-density parity-check (LDPC) code and a repetition code (REP), this way achieving near Gaussian MAC (GMAC) capacity performance while coping with the dynamics of the MAC system. The joint optimization of the LDPC and REP codes is addressed by matching the analytical extrinsic information transfer (EXIT) functions of the sub-optimal multi-user detector (MUD) and the channel code for a specific and static MAC system, achieving near-GMAC capacity. We show that the near-capacity performance can be flexibly maintained with the same LDPC code regardless of the variations in the number of users and power levels. This flexibility (or elasticity) is provided by the REP code, acting as “user-load and power equalizer”, dramatically simplifying the practical implementation of NOMA schemes, as only a single LDPC code is needed to cope with the dynamics of the MAC system.

Universal Filtered OFDM (UF-OFDM) exhibits better spectral properties compared to the classic OFDM modulation technique. One of the drawbacks of multicarrier modulation (MCM) is its high Peak to Average Power Ratio (PAPR), challenging power amplifier design. In this paper, the PAPR of UF-OFDM signals is analyzed mathematically and then verified by numerical simulations. It is shown, analytically as well as by simulation, that the PAPR of UF-OFDM signals is higher than that of OFDM signals due to the FIR-filtering. Moreover, a simple approximated PAPR relation between both signals is found and accurately matches with simulation. To reduce the PAPR, a simple clipping algorithm along with DFT precoding is investigated in UF-OFDM systems with low complexity transceiver implementation, and compared with classic CP-OFDM/SC-FDMA systems under various system settings of both synchronous and asynchronous multiuser transmission. The link level simulation with typical LTE parameters shows that UF-OFDM performs slightly worse than OFDM with perfect time and frequency synchronization, while significant SNR gain of more than 2 dB can be achieved with relaxed synchronization.

In this paper, a novel iterative MIMO subspace detection method is proposed to approach the maximum-likelihood (ML) receiver performance while keeping the computational complexity scalable for MIMO systems with large number of transmit and receive antennas. By dividing the signal detection problem for a large MIMO system into subspaces with smaller size, the complexity of applying a per-subspace ML receiver is much lower while near ML performance may still be achieved in combination with an iterative parallel interference cancellation unit. It is shown that, for equal number of transmit and receive antennas, the complexity of the proposed method is cubic with the number of transmit antennas. A flexible complexity#x002F;performance trade-off can be obtained by varying the subspace size. Even for small subspace dimensions, close to ML performance can be achieved, resulting in low complexity. The performance of this method is assessed in terms of bit error rate and achievable mutual information, and compared to conventional MIMO detection methods using the zero-forcing (ZF) or minimum mean squared error (MMSE) criterion, as well as the successive interference cancellation (SIC) approach. Furthermore, the convergence behavior of this iterative detection method is analyzed using a new variant of the EXIT-Chart based on the mutual information of equivalent hard output channels, i.e., a binary symmetric channel (BSC) model.

Universal Filtered Multi-Carrier (UFMC) is a novel multi-carrier modulation technique which can be seen as a generalization of filtered OFDM and filter bank based multicarrier (FBMC-FMT). Being a candidate waveform technology for 5G wireless systems, it combines the simplicity of OFDM with the advantages of FBMC. The FIR-filter, used in UFMC to filter a group of subcarriers, is a key design parameter to gain more robustness in relaxed synchronization conditions, i.e. timefrequency misalignment. It was shown in previous work that very significant SIR improvement can be achieved for UFMC by optimizing the FIR-filter, taking carrier frequency offset into account. In this paper, we optimize the FIR-filter design in UFMC by taking both carrier frequency and timing offset into account in an uplink multi-user FDMA scenario. From the simulation results, up to 3.6 dB SIR improvement can be achieved with the optimized FIR filter compared to UFMC with non-optimized Dolph-Chebyshev filter and 15.1 dB SIR gain against classical CP-OFDM system respectively, provided that the normalized carrier frequency and timing offset are uniformly distributed in the interval ±5%.

Universal Filtered Multi-Carrier (UFMC, a.k.a. UF-OFDM) is a novel multi-carrier modulation technique, which aims at replacing OFDM for next generation wireless communication systems (5G). It is a generalization of OFDM and filter bank based multi-carrier (FBMC-FMT), which combines the advantages of OFDM and FBMC while avoiding its main drawbacks. UFMC is shown to be more robust in relaxed synchronization conditions i.e. time-frequency misalignment compared to conventional CP-OFDM systems. As required in potential scenarios of 5G systems, UFMC is more efficient to support short uplink bursts communications. Without the insertion of cyclic prefix, we investigate the procedure and performance of pilot-aided channel estimation for UFMC in an uplink multi-user FDMA scenario and show that almost the same performance as CP-OFDM can be achieved despite the lack of cyclic prefix. In case of timing and frequency offset, UFMC shows its robustness over CP-OFDM in terms of symbol error rate (SER). Simulation results show that the error floor is reduced applying UFMC for considered different types of channels.