Multi-user relay networks with massive MIMO

The advantages envisioned from using large antenna arrays have made massive multiple- input multiple-output systems (also known as massive MIMO) a promising technology for future wireless standards. Despite the advantages that massive MIMO systems provide, increasing the number of antennas introduces new technical challenges that need to be resolved. In particular, symbol detection is one of the key challenges in massive MIMO. Obtaining accurate channel state information (CSI) for the extremely large number of chan- nels involved is a difficult task and consumes significant resources. Therefore for Massive MIMO systems coherent detectors must be able to cope with highly imperfect CSI. More importantly, non-coherent schemes which do not rely on CSI for symbol detection become very attractive. Expectation propagation (EP) has been recently proposed as a low complexity algo- rithm for symbol detection in massive MIMO systems , where its performance is evaluated on the premise that perfect channel state information (CSI) is available at the receiver. However, in practical systems, exact CSI is not available due to a variety of reasons in- cluding channel estimation errors, quantization errors and aging. In this work we study the performance of EP in the presence of imperfect CSI due to channel estimation er- rors and show that in this case the EP detector experiences significant performance loss. Moreover, the EP detector shows a higher sensitivity to channel estimation errors in the high signal-to-noise ratio (SNR) regions where the rate of its performance improvement decreases. We investigate this behavior of the EP detector and propose a Modified EP detector for colored noise which utilizes the correlation matrix of the channel estimation error. Simulation results verify that the modified algorithm is robust against imperfect CSI and its performance is significantly improved over the EP algorithm, particularly in the higher SNR regions, and that for the modified detector, the slope of the symbol error rate (SER) vs. SNR plots are similar to the case of perfect CSI. Next, an algorithm based on expectation propagation is proposed for noncoherent symbol detection in large-scale SIMO systems. It is verified through simulation that in terms of SER, the proposed detector outperforms the pilotbased coherent MMSE detector for blocks as small as two symbols. This makes the proposed detector suitable for fast fading channels with very short coherence times. In addition, the SER performance of this detec- tor converges to that of the optimum ML receiver when the size

Massive multiple-input multiple-output (MIMO) technology is expected to achieve significant gains in both signal-to-noise-plus-interference ratio (SINR) and throughput for 5G cellular wireless networks. Efficient and highly accurate channel state information (CSI) acquisition at the base stations (BS) is essential to achieve the potential benefits of massive MIMO systems. However, the inadequate number of orthogonal pilot sequences used for CSI estimation leads to erroneous channel estimation as it causes interference between pilot sequences. This phenomenon is coined pilot contamination and severely limits the system performance. Therefore, we address in this paper the pilot contamination problem in massive MIMO Cloud-Radio Access Networks systems. Leveraging on a real telecom operator data delivered by Call Detail Records (CDR), our objective is to maximize the average uplink achievable rate by reducing the effect of pilot contamination in massive MIMO Cloud-Radio Access Networks (C-RAN). As such a problem is a non-linear integer problem that has no solution in polynomial time, we develop a two-stage solution to solve it. First, a coalition game is proposed where Remote Radio Heads (RRHs) gather into clusters with random user-pilot allocation. Then, two greedy heuristics are applied to match each user in the cluster with a given pilot. The goal is to further improve the average uplink rate achieved in the first stage. Simulation results show that our heuristic solutions for pilot contamination mitigation outperform the traditional pilot allocation solution and a state-of-the-art pilot allocation scheme based on large-scale fading in terms of average uplink achievable rate and SINR.

In the first part of the thesis we investigate bandwidth allocation in next generation cellular systems employing relays similar to LTE advanced systems with type-I relays. We jointly optimize the bandwidth and power usage under constraints on required rate, bandwidth and transmit power. We study scenarios wherein, the relay acts as a forwarder for multiple User Equipments (UEs/users) in both uplink and/or downlink. This includes scenarios when the relay has its own data to send along with forwarding the data of other users. We examine the weighted power minimization problem for relaying with multiple users. We also show specifi c results with N user scenario and also single user case in order to understand how the bandwidth and power are allocated. Numerical evaluations with N users on a three sector LTE-A cell employing Fractional Frequency Reuse (FFR) indicate that power savings of at least 3 dB can be achieved by optimizing over both bandwidth and power. Base stations with a large number of transmit antennas have the potential to serve a large number of users simultaneously at higher rates. They also promise a lower power consumption due to coherent combining at the receiver. However, the receiver processing in the uplink relies on the channel stimates which are known to su ffer from pilot contamination. In the second part of the thesis, we perform an uplink large system analysis of multi-cell multi-antenna system when the receiver employs a matched fi ltering and MMSE fi ltering with a pilot contaminated estimate. We find the asymptotic Signal to Interference plus Noise Ratio (SINR) as the number of antennas and number of users per base station grow large while maintaining a fixed ratio. To do this, we make use of the similarity of the uplink received signal in a multi-antenna system to the representation of the received signal in CDMA systems. The asymptotic SINR expression for both matched fi lter and the MMSE fi lter explicitly captures the e ffect of pilot contamination and that of interference averaging. This also explains the SINR performance of receiver processing schemes at di fferent regimes such as instances when the number of antennas are comparable to number of users as well as when antennas exceed greatly the number of users. Specifi cally, we explore the scenario where the number of users being served are comparable to the number of antennas at the base station. It is seen that MMSE fi lter is capable of suppressing the in-cell interference and that the interference power due to pilot contamination is the same as in a matched fi lter with a pilot contaminated estimate. We find the expression for the amount of interference suppression obtained using an MMSE filter which is an important factor when there are signi ficant number of users in the system as compared to the number of antennas. We validate the asymptotic expression through simulations and compare with an MMSE fi lter with a perfect estimate. Simulation results for achievable rate is close to theory for even a 10-antenna base station with 3 or more users per cell. In a typical set up, in terms of the five percentile SIR, the MMSE fi lter is shown to provide signifi cant gains over matched fi ltering and is within 5 dB of MMSE fi lter with perfect channel estimate. We also show that the achievable rates are within a 1 bit/symbol of the MMSE with perfect estimate when the number of users is comparable to the number of antennas.

Reconfigurable Intelligent Surface (RIS) is an emerging technology that can improve the spectrum and energy efficiency of next-generation wireless networks. However, attaining accurate channel state information (CSI) for the cascaded RIS channel is particularly challenging. Imperfect CSI is a major bottleneck to achieving the spectral efficiency benefit of RIS-assisted networks. Rate splitting (RS), a promising multiple access technology, has been shown to be able to achieve an improved spectrum efficiency and be robust to channel uncertainties. This paper investigates the interplay between RIS and RS by considering a RIS-assisted RS beamforming problem. Active beamforming at the base station (BS) and passive beamforming at the RIS are jointly considered to maximize the minimum user rate under both the perfect CSI case and the imperfect CSI case. A block coordinate descent (BCD) algorithm is developed to solve this non-convex problem. Compared with the conventional semi-definite relaxation (SDR) approach, the proposed method does not require that the covariance matrix of the common beamforming vector be rank-one. Moreover, we present theoretical results to help reveal the impact of the system parameters and explain the performance gain resulting from the integration of RIS and RS. Extensive simulation results are also provided to show that RIS-assisted RS can improve the max-min rate performance significantly compared with conventional multiple access technologies, such as non-orthogonal multiple access (NOMA) and space division multiple access (SDMA) with/without RIS, especially in overloaded systems. With the proposed method, RS shows great potential in combating realistic CSI errors in RIS-assisted networks.

In this paper, we investigate the impact of the outdated Channel State Information (CSI) and the Co-Channel Interference (CCI) on the performance of Transmit Antenna Selection with Selective Combining (TAS/SC) in a dual-hop amplify-and-forward (AF) Multiple-Input Multiple-Output (MIMO) relay network. We derive the exact closed-form and asymptotic expressions for the outage probability in the cases of perfect and outdated CSI, respectively. The simulation results match the theoretical analysis well. The findings suggest that the outdated CSI and CCI have significant impacts on the outage probability of an AF MIMO relay system with TAS/SC.

We consider the problem of optimizing the allocation of available energy across training and data symbols under linear precoding in multiuser downlink systems with imperfect channel state information (CSI). Our figure of merit is the sum rate across all users. This paper derives a lower bound on achievable rate under linear precoding and extends existing precoder designs to the case of imperfect CSI. Optimality and separability results for the energy allocation and precoder design problems that were found previously for sum-MSE minimization are extended to the problem of sum-rate maximization when channels are modelled using uncorrelated Rayleigh block fading with equal variances of the fading coefficients. Simulation results suggest significant improvements in achievable rate under the proposed algorithm.

Due to cell planning in a cellular communication network, it is difficult for a mobile user in a cell to get ranging measurements from other neighboring cells. Consequently, it is necessary to enhance signal sensitivity using long integration techniques so that the user position is obtained by trilateration. In order to maximize integration gain in coherent/noncoherent hybrid long integration, it is desirable to make SNR (signal to noise ratio) after coherent integration become as large as possible. Because SIR (signal to interference ratio) is not improved by the long integration, however, it is needed to mitigate CCI (Co-Channel Interference) so that the resultant hearability can be enhanced for weak signals. This paper presents a hybrid long integration scheme in presence of CCI. SNIR (signal to noise plus interference ratio) is employed to explain the loss induced by interference as well as noise. Together with interference cancellation and residual frequency estimation technique, design procedure of hybrid long integration is proposed to maximize SNIR. Simulation results show that hearability is greatly improved at most of cell coverage when the proposed method is used.

For the next generation of wireless communication network, a heterogeneous network architecture with macro cells, small cells, and relays offers numerous advantages, such as higher spectrum efficiency, better fairness in resource allocation, and energy efficient usage as well as optimal coverage. However, this approach encounters various network management challenges, including interference mitigation techniques. In this paper, we consider a multi-user half-duplex amplify-and-forward-MIMO relay system, where a macro basis station communicates with edge cell users via relays and each node has multiple antennas. In this context, we propose two interference alignment (IA) schemes, for which a hybrid approach of the problem formulation based on zero-forcing (ZF) and minimum-mean-square-error optimization criteria was developed to deal with interferences in perfect and imperfect channel state information (CSI) cases. In the case of perfect CSI, simulation results show that this approach provides a SNR gain of about 4 dB regarding BER performance in comparison to that achieved by the reference approach, where all filters are determined solely based on ZF criterion. Furthermore, the achieved capacity and effective signal-to-interference-plus-noise ratio at each edge node are improved by around 5 dB. Having CSI errors, the system performance is significantly improved using the robust design IA approach by minimizing the expected value of cost functions.

In this paper, the performance analysis of two different diversity models in presence of multiple interferers and co-channel interference is presented. Arbitrary number of received signals are examined and processed using these diversity techniques. The performance analysis is presented for a Partitioned Selection Diversity Combiner (PSDC) which is an Advanced Diversity Combiner (ADC) consisting of $L$ Selection Combiners (SC) followed by a Maximal Ratio Combiner (MRC). The results are also presented for another ADC consisting of a Generalized Selection Combiner (GSC) followed by an MRC. Both the models are analyzed in the presence of co-channel interference (CCI) over Nakagami-m fading channels. The signal to interference plus noise ratio (SINR) is derived. Using the obtained expressions of SINR, the Average bit error rate (ABER) expression for differential phase shift keying (DPSK) and non-coherent frequency shift keying (NCFSK) modulation techniques are derived. The ABER results are plotted and comparison is made between the two diversity models. Numerical and simulation results are done.

In this paper, we investigate methods for reducing the likelihood that a message transmitted between two multi-antenna nodes is intercepted by an undetected eavesdropper. In particular, we focus on the judicious transmission of artificial interference to mask the desired signal at the time it is broadcast. Unlike previous work that assumes some prior knowledge of the eavesdropper's channel and focuses on maximizing secrecy capacity, we consider the case where no information regarding the eavesdropper is available, and we use signal-to-interference-plus-noise-ratio (SINR) as our performance metric. Specifically, we focus on the problem of maximizing the amount of power available to broadcast a jamming signal intended to hide the desired signal from a potential eavesdropper, while maintaining a prespecified SINR at the desired receiver. The jamming signal is designed to be orthogonal to the information signal when it reaches the desired receiver, assuming both the receiver and the eavesdropper employ optimal beamformers and possess exact channel state information (CSI). In practice, the assumption of perfect CSI at the transmitter is often difficult to justify. Therefore, we also study the resulting performance degradation due to the presence of imperfect CSI, and we present robust beamforming schemes that recover a large fraction of the performance in the perfect CSI case. Numerical simulations verify our analytical performance predictions, and illustrate the benefit of the robust beamforming schemes.

The feasibility of implementing non-orthogonal multiple access (NOMA) in massive multiple-input multiple-output (MIMO) downlink with distributed antenna arrays is investigated. The achievable downlink rates are derived for two channel state information (CSI) cases, namely (i) estimated uplink CSI at the access points (APs) via user uplink pilots and statistical CSI at the users, and (ii) estimated uplink CSI at the APs via uplink user pilots and estimated downlink CSI at the users via downlink pilots beamformed by the APs. The trade-off between the number of served user nodes and their achievable rates is investigated. The adverse effects of imperfect successive interference cancellation (SIC) and detection uncertainty on the achievable downlink rates are quantified. We show that the achievable downlink rate of NOMA can be inferior to that of the orthogonal multiple-access (OMA) counterpart in the low-user regime. This is a direct consequence of residual interference caused by intra-cluster pilot contamination and error propagation from imperfect SIC. However, the proposed massive MIMO NOMA downlink outperforms the OMA counterpart in the highuser regime in terms of the achievable downlink rate. Moreover, the impact of downlink pilots on the sum rate is also investigated.

We analyze relay selection for an underlay cognitive radio (CR) two-way relay network (TWRN) with zero-forcing (ZF) transmission and receiving. The source and the destination nodes are massive multiple-input multiple-output (MIMO) enabled. Relays will perform amplify and forwarding (AF) while the destination and source nodes perform self interference cancellation. We first obtain asymptotic signal-to-interference-plus-noise ratio (SINR) values under the power scaling at the relay and end nodes. Then, we derive optimal power allocation schemes for the end nodes to satisfy the interference constraints at the primary user (PU). Based on these optimal values, we analyze the effect of relay selection on the sum rate. With the use of massive MIMO, the SINR and the sum rate will only depend on the pathloss coefficients of the channels and average noise levels. Thus, the relay selection can be done at the deployment stages of the system and most of the time it simplifies to selection of the relay with the highest number of antennas. Our simulation results validate the analytical asymptotic results and qualify CR massive MIMO TWRNs as a possible candidate for future wireless systems.

In order to meet the demands of “Internet above the clouds,” we propose a multiple-antenna aided adaptive coding and modulation (ACM) for aeronautical communications. The proposed ACM scheme switches its coding and modulation mode according to the distance between the communicating aircraft, which is readily available with the aid of the airborne radar or the global positioning system. We derive an asymptotic closed-form expression of the signal-to-interference-plus-noise ratio (SINR) as the number of transmitting antennas tends to infinity, in the presence of realistic co-channel interference and channel estimation errors. The achievable transmission rates and the corresponding mode-switching distance-thresholds are readily obtained based on this closed-form SINR formula. Monte-Carlo simulation results are used to validate our theoretical analysis. For the specific example of 32 transmit antennas and four receive antennas communicating at a 5-GHz carrier frequency and using 6-MHz bandwidth, which are reused by multiple other pairs of communicating aircraft, the proposed distance-based ACM is capable of providing as high as 65.928-Mb/s data rate when the communication distance is less than 25 km.

Massive multiple-input multiple-output (MIMO) systems have attracted much attention lately due to the many advantages they provide over single- antenna systems. Owing to the many antennas, low- cost implementation and low power consumption per antenna are desired. To that end, massive MIMO structures with one-bit analog-to-digital converters (ADC) have been investigated in many studies. However, the effect of a strong interferer in the adjacent band on one-bit quantized massive MIMO systems have not been examined yet. In this study, we analyze the performance of uplink massive MIMO with one-bit ADCs under frequency selective fading with orthogonal frequency division multiplexing (OFDM) in the perfect and imperfect receiver channel state information cases. We derive analytical expressions for the bit error rate and ergodic rate. We show that the interfering band can be suppressed by increasing the number of antennas or the oversampling rate when a zero-forcing receiver is employed.

Full-duplex amplify-and-forward relay system with direct link: Performance analysis and optimization