Cell-free massive MIMO (CF-mMIMO), which cooperatively utilizes a large number of antennas deployed over a communication area, has been attracting great attention as an important technology for realizing 5G-advanced and 6G systems. Recently, to ensure system scalability and mitigate inter-user interference in CF-mMIMO, a user-centric (UC) approach was investigated. In this UC approach, user-centric antenna-sets are formed by selecting appropriate antennas for each user, and postcoding is applied to reduce the strong interference from users whose antenna-sets overlap. However, in very high user density environments, since the number of interfering users increases due to increased overlapping of antenna-sets, the achievable link capacity may degrade. In this paper, we propose a user-cluster-centric (UCC) approach, which groups neighborhood users into a user-cluster and associates the predetermined number of antennas to this user-cluster for spatial multiplexing. We derive the uplink postcoding weights and explain the effectiveness of the proposed UCC approach in terms of the computational complexity of the weight computation. We also compare the uplink user capacities achievable with UC and UCC approaches by computer simulation and clarify situations where the UCC approach is effective. Furthermore, we discuss the impact of the number of interfering users considered in the zero-forcing and minimum mean square error postcoding weight computation on the user capacity.

In this paper, the uplink performance of Multi-User Multiple Input Multiple Output (MU-MIMO) Zero Forcing (ZF) receiver is investigated over correlated Rayleigh fading channels with channel estimation error. A mathematical expression for the sub-streams' output Signal to Noise Ratio (SNR) with transmit and receive-correlation is derived in the presence of erroneous channel estimates. Besides, an approximate and accurate expression for the Bit Error Rate (BER) of ZF receiver for 16-Quadrature Amplitude Modulation (QAM) with transmit-correlation is deduced in terms of the hypergeometric function. Subsequently, the developed analytical BER is verified by Monte-Carlo trails accounting various system parameters. The simulation results indicate that ZF receiver's BER relies solely on the transmit-correlation for the same number of transmit and receive-antennas at higher average SNR values per transmitted symbol (Es/N0). Also, a logarithmic and exponential growth in the BER is observed with an increase in the Mean Square estimation Error (MSE) and correlation coefficient, respectively.

In this paper, we propose an efficient regularized zero-forcing (RZF) precoding method that has lower hardware resource requirements and produces a shorter delay to the first transmitted symbol compared with truncated polynomial expansion (TPE) that is based on Neumann series in massive multiple-input multiple-output (MIMO) systems. The proposed precoding scheme, named matrix decomposition-polynomial expansion (MDPE), essentially applies a matrix decomposition algorithm based on polynomial expansion to significantly reduce full matrix multiplication computational complexity. Accordingly, it is suitable for real-time hardware implementations and high-mobility scenarios. Furthermore, the proposed method provides a simple expression that links the optimization coefficients to the ratio of BS/UTs antennas (β). This approach can speed-up the convergence to the matrix inverse by a matrix polynomial with small terms and further reduce computation costs. Simulation results show that the MDPE scheme can rapidly approximate the performance of the full precision RZF and optimal TPE algorithm, while adaptively selecting matrix polynomial terms in accordance with the different β and SNR situations. It thereby obtains a high average achievable rate of the UTs under power allocation.

In a multi-cell MIMO system, the rate of edge users is limited by the inter-cell co-channel interference. The CoMP scheme which includes Joint Process (JP) and Coordinated Scheduling/Beamforming (CS/CB) was developed to reduce the inter-cell interference and enhance the edge rate. Because CS/CB can alleviate the overhead of network, it gains attention recently. In this paper, a modified zero forcing beamforming (ZFBF) is applied to downlink transmission in a two-cell MIMO system. In order to enhance system sum rate, a novel coordinated user scheduling algorithm is proposed. Firstly, we select users with high correlation among cross-channels as candidates, and then group users from candidates with high orthogonality among direct-channels, and match user groups in different cells as the final scheduling group pair. Simulations show that the proposed algorithm can achieve a higher system sum rate with low complexity than traditional scheduling algorithms.

In this paper, we investigate unitary precoder design for multiple-input multiple-output (MIMO) multicasting, where multiple common data streams are sent to a group of users. Assuming that zero-forcing decision feedback equalizers (ZF-DFE) are adopted at the receiver side, we can convert the multicast channel into multiple parallel subchannels. To improve the receiving quality of all data streams, we focus on maximizing the minimal signal-to-noise ratio (SNR) of all data streams. To effectively handle this non-convex optimization problem, we first consider the special case of two data streams and derive the closed-form solution of the SNR vectors for both subchannels. Based on these results, a gradient-based iterative algorithm is developed for the proposed precoder design. For the general case, a Givens rotation-based iterative algorithm is proposed, where at each iteration the original problem of unitary precoder design is transformed into a dual-stream subproblem. Hence it can be solved efficiently by the gradient-based iterative algorithm. Finally, simulation results are presented to demonstrate the outstanding performance of the proposed design.

In this paper, an adaptive expansion strategy (AES) is proposed for multiple-input/multiple-output (MIMO) detection in the presence of circular signals. By exploiting channel properties, the AES classifies MIMO channels into three types: excellent, average and deep fading. To avoid unnecessary branch-searching, the AES adopts single expansion (SE), partial expansion (PE) and full expansion (FE) for excellent channels, average channels and deep fading channels, respectively. In the PE, the non-circularity of signal is exploited, and the widely linear processing is extended from non-circular signals to circular signals by I (or Q) component cancellation. An analytical performance analysis is given to quantify the performance improvement. Simulation results show that the proposed algorithm can achieve quasi-optimal performance with much less complexity (hundreds of flops/symbol are saved) compared with the fixed-complexity sphere decoder (FSD) and the sphere decoder (SD).

This paper presents a novel decision feedback equalizer (DFE) with block delay detection for the joint transceiver design that uses channel state information (CSI). The block delay detection in the proposed DFE offers a degree of freedom for optimizing the precoder of the transmitter, provided the transmission power is constrained. In the proposed DFE, the feedforward matrix is devised to enable a block-based equalizer that can be cooperated with an intrablock decision feedback equalizer for suppressing the intersymbol interference (ISI) for the transmitted block with a certain block delay. In this design, the interblock interference (IBI) for the delay block is eliminated in advance by applying the recently developed oblique projection framework to the implementation of the feedforward matrix. With knowledge of full CSI, the block delay and the associated block-based precoder are jointly designed such that the average bit-error-rate (BER) is minimized, subject to the transmission power constraint. Separate algorithms are derived for directly determining the BER-minimized block delays for intrablock minimum mean-squared error (MMSE) and zero-forcing (ZF) equalization criteria. Theoretical derivations indicate that the proposed MMSE design simultaneously maximize the Gaussian mutual information of a transceiver, even under the cases of existing IBI. Simulation results validate the proposed DFE for devising an optimum transceiver with CSI, and show the superior BER performance of the optimized transceiver using proposed DFE. Relying on analytic results and simulation cases also builds a sub-optimum MMSE design of the proposed DFE using the BER-minimized block delay for ZF criterion, which exhibits almost identical BER performance as the proposed MMSE design in most of the signal-to-noise ratio (SNR) range.

The Multiple-Input Multiple-Output (MIMO) Zero-Forcing (ZF) receiver requires accurate Channel State Information (CSI), which is impacted by channel estimation error, to perform properly. Moreover, interference occurs due to the change of channel coefficients between the channel estimation events in fading channels. Thus, in practice, both channel estimation error and interference greatly influence Bit Error Rate (BER) performance. In this letter, we derive an Signal-to-Interference-and-Noise Ratio (SINR) expression considering both channel estimation error and interference and develop approximate closed-form BER expressions of M-PSK and M-QAM for the MIMO ZF receiver in Nakagami-m fading channels. We then analyze the effects of channel estimation error, interference, and the numbers of transmit and receive antennas.

In this letter, a quantization error-aware Tomlinson-Harashinma Precoding (THP) is proposed based on the equivalent zero-forcing (ZF) criterion in Multiuser Multiple-Input Single-Output (MU-MISO) systems with limited feedback, where the transmitter has only quantized channel direction information (CDI). This precoding scheme is robust to the channel uncertainties arising from the quantization error and the lack of channel magnitude information (CMI). Our simulation results show that the new THP scheme outperforms the conventional precoding scheme in limited feedback systems with respect to Bit Error Ratio (BER).

This letter presents a criterion for selecting a transmit antenna subset when ZF detectors followed by Rake combiners are employed for spatial multiplexing (SM) ultra-wideband (UWB) multiple input multiple output (MIMO) systems. The presented criterion is based on the largest minimum post-processing signal to interference plus noise ratio of the multiplexed streams, which is obtained on the basis of QR decomposition. Simulation results show that the proposed antenna selection algorithm considerably improves the BER performance of the SM UWB MIMO systems when the number of multipath diversity branches is not so large and thus offers diversity advantages on a log-normal multipath fading channel.

In this paper, we propose a full-duplex relay (FDR) based on a zero-forcing beamforming (ZFBF) for a multiuser MIMO system. The ZFBF is employed at the base station to suppress both the self-interference of the relay and the multiuser interference at the same time. Numerical results show that the proposed FDR can enhance the sum rate performance as compared to the half-duplex relay (HDR), if sufficient isolation between the transmit and receive antennas is ensured at the relay.

In this letter, we consider a novel ultra-wideband (UWB) spatial multiplexing (SM) multiple input multiple output (MIMO) structure, which consists of prerake diversity combiners in the transmitter and a zero forcing (ZF) detector in the receiver. For a UWB SM MIMO system with N transmit antennas, M receive antennas, and L resolvable multipath components, it is shown that the proposed prerake combining-based MIMO detection scheme has the diversity order of (LN-M+1) and its BER performance is analytically presented in a log-normal fading channel and also compared with that of a rake combining-based ZF scheme.

In the conventional multi-input multi-output (MIMO) communication systems, most of the antenna selection methods considered are suitable only for spatially separated uni-polarized system under Rayleigh fading channel in non-line of sight (NLOS) condition. There have a few antenna selection schemes for the cross-polarized system in LOS condition and Ricean fading channel, and no antenna selection scheme for the MIMO channel with both LOS and NLOS. In the practical MIMO channel case, influence of LOS and NLOS conditions in the channel can vary from time to time according to the channel parameters and user movement in the system. Based on these influences and channel condition, uni-polarized system may outperform a cross-polarized. Thus, we should consider this kind of practical MIMO channel environment when developing the antenna selection scheme. Moreover, no research work has been done on reducing the complexity of antenna selection for this kind of practical MIMO channel environment. In this paper, reduced complexity in antenna selection is proposed to give the higher throughput in the practical MIMO channel environment. In the proposed scheme, suitable polarized antennas are selected based on the calculation of singular value decomposition (SVD) of channel matrix and then adaptive bit loading is applied. Simulation results show that throughput of the system can be improved under the constraint of target BER and total transmit power of the MIMO system.

Precoding techniques can be introduced into relay systems due to the similarity between relay systems and traditional multi-input-multi-output (MIMO) systems. A channel state information feedback scheme is firstly presented for the MIMO relay system in this letter, where the zero-forcing relaying protocol is proposed to be used so that the information of the equivalent channel and the relaying noise can be compressed into two coefficients. With the proposed feedback scheme, the distributed precoding is presented to be applied through two continuous transmitted vectors of the source node while the co-channel interference cancellation equalizer is used in the destination node. The system outage probability can be improved with the precoding in the source node. Furthermore, various spatial data rates can be conveniently supported by the proposed distributed spatial-temporal precoding method.

The performance of ultra-wideband (UWB) multiple input multiple output (MIMO) receiver based on the RAKE maximal ratio combiner (MRC) followed by a zero forcing (ZF) detector is analytically examined. For a UWB MIMO system with NT transmit antennas, NR receive antennas, and L resolvable multipath components, the proposed MIMO detection scheme is shown to have the diversity order of LNR-NT+1 and its analytical error rate expression is presented in a log-normal fading channel. We also compare the analytical BERs with the simulated results.

In this letter, a new joint precoding and decoding design scheme for multiuser MIMO downlink is proposed which dispenses with iterative operations and can achieve better performance. This scheme introduces zero-force processing into minimum mean square error (MMSE) design scheme to avoid iterative operations. We derived closed-form precoders and decoders and transmit power allocation strategy of proposed design scheme, validated performance of proposed design scheme by computer simulation. The simulation results show that the proposed design scheme can achieve better bit error rate (BER) and sum capacity performance compared to an existing non-iterative design scheme.

We describe a channel-vector quantization scheme that is suitable for multiple stream transmission per user in zero-forcing beamforming (ZFBF) multiuser multiple-input and multiple output (MU-MIMO) systems with finite rate feedback. Multiple subsets of a channel matrix are quantized to vectors from random vector codebooks for finite rate feedback. The quantization vectors with an angle difference that is closer to orthogonal are then selected and their indexes are fed back to the transmitter. Simulation results demonstrate that the proposed scheme achieves a better average throughput than that serving a single stream per user when the number of active users is smaller than the number of transmit antennas and that it provides an average throughput close to that serving a single stream per user when the number of users is equal to the number of transmit antennas.

An adaptive zero forcing maximum likelihood soft input soft output (AZFML-SISO) detector for multiple input multiple output (MIMO) wireless systems is presented. Its performance in an iterative MIMO receiver is analyzed. The AZFML-SISO detector calculates the soft outputs, applying the ML approach to the list that contains only those signal vectors limited by a hypersphere around the zero forcing (ZF) solution. The performance of the algorithm is evaluated on a communication system based on the standard for single carrier broadband wireless communication IEEE 802.16, with three transmit and three receive antennas. It is shown by computer simulation that the computational complexity in an average sense of the receiver running the AZFML-SISO algorithm is reduced by 90% at the SNR values of 30 dB and by 50% for SNR values of 15 dB in comparison to the receiver with an ML detector, while the system performance degrades by less than 1 dB.

In this letter, we propose a novel singular value decomposition zero-forcing beamforming (SVD-ZFBF) relaying scheme in the multiuser downlink MIMO broadcasting channel with fixed relays. Based on the processing scheme, we apply SUS [5] to select users at the relay station (RS) and develop a joint power allocation strategy at the base station (BS) and RS. By increasing the power at RS or selecting active users to obtain more multiuser diversity, SVD-ZFBF can approach an upper bound and outperform SVD-ZFDPC [1] with much lower complexity. Moreover, we show that the noise power ratio of RS to users significantly impacts the performance.

A modified successive interference cancellation (SIC) algorithm for orthogonal frequency division multiplexing (OFDM) system is presented. The presented modified SIC algorithm makes use of an index sequence to avoid the subcarriers re-ordering calculation. Furthermore, by combining the SIC with the conventional zero-forcing (ZF) detection, computation complexity of the presented algorithm can be significantly reduced and meanwhile excellent performance can be maintained.