Millimetre-wave (mmWave) communications have been regarded as a key technology for the next-generation cellular systems since the huge available bandwidth can potentially provide the rates of multiple gigabits per second. Conventional precoding and combining techniques are impractical at mmWave scenarios due to manufacturing costs and power consumption. Hybrid alternatives have been considered as a promising technology to provide a compromise between hardware complexity and system performance. This study examines, using a semi-analytic approach, the downlink performance of massive MU-MIMO mmWave systems in terms of the bit error rate (BER). Also, a general expression is derived to estimate an upper bound/approximation to the BER performance via the Monte Carlo method, which can be used for any hybrid precoder/combiner, modulation and different data detectors. Numerical results evidence that the approximate BER expressions provide values very close to the ones obtained through simulation using only two statistical moments related to parameters of the system, mean and variance.

Today's, a promising solution, namely wireless network-on-chip (WiNoC) is utilized in multi-core systems to overcome the constraints of conventional on-chip networks. In WiNoC architectures, wireless routers (WRs) provide high capacity wireless links to reduce the latency of multi-hop communications. However, the buffer size of the WR antenna is limited, and under heavy traffic loads, it's filled and congestion occurs. On the other hand, network performance is degraded severely in the presence of head-of-line (HOL) blocking. Therefore, flow control and scheduling mechanisms are vital for improving the performance of WiNoCs. In this study, a flow control scheme based on an active queue management algorithm, and a priority-based scheduling strategy are suggested. The proposed mechanisms are evaluated under uniform and Bit-complement traffic patterns with different packet injection rate. The simulation results show that the proposed schemes have a significant impact on performance parameters, such as latency and throughput. Moreover, the saturation packet injection rate in WiNoC with four WRs is improved to about 33% under uniform traffic and is increased up to about 50% under the Bit-complement traffic pattern. This is increased by 16 and 50% in WiNoC with 16 WRs for uniform and Bit-complement traffic patterns, respectively, compared to the conventional WiNoCs.

In this study, a relay assisted order energy harvesting-based non-orthogonal multiple access (NOMA) network is considered where the relay harvests energy from radio frequency signal of the source. A transmit antenna selection scheme is considered at the source under imperfect channel state information (CSI). The outage probability of order NOMA network is analysed and a closed-form expression of it is obtained. A comparative performance study is carried out with perfect and imperfect successive interference cancellation at the receiver. The impact of a number of antennas available at the source on outage performance and the effect of imperfect CSI on the outage performance are also presented in this work. The upper limit of the order of the NOMA network to be supported for a given threshold signal to interference plus noise ratio (SINR) is also estimated.

In this study, the authors propose a novel architecture based on the combination of peak-to-average power ratio (PAPR) reduction with digital beamforming (BF) for mm-wave massive multiple-input multiple-output (MIMO) systems. In order to keep the power amplifiers (PAs) working at the same input back-off thus maximising the system power efficiency, they propose to perform time-domain transmit beam-steering by adding progressive time delays to the signals at each antenna element, while keeping the amplitude weights unitary. They show that these time delays can be obtained with a finite impulse response filter implementation of time-domain fractional delay filter structures such as Lagrange interpolation polynomials. They also introduce an analysis on the PAPR of the interpolated signals, where they derive an upper bound to it and show that its value is similar to that of the signal at the input of the interpolation filters, showing the feasibility of the proposed method. In addition, they present a detailed analysis where they show that a significant reduction in computational complexity is obtained when compared to frequency-domain BF. Simulation results validate that the novel proposed scheme combining PAPR reduction and digital BF offers high-precision beam-steering maintaining reduced PAPR in the delayed signals fed to the antennas.

Spectrum sensing plays a key role in cognitive radio technology to acquire information on the occupancy status of the channel. Cyclostationary spectrum sensing is considered one of the most promising approaches. However, its performance is severely degraded by a mismatch between the actual and the nominal cyclic frequency [i.e. cyclic frequency offset (CFO)]. This is particularly true for vehicular networks, due to the high mobility and particularly to the presence of a non-zero radial acceleration between the transmitter and the receiver that makes the signal filtered out by the Doppler channel chirped, thus introducing the CFO. Consequently, the signal to be detected has to be properly modelled as a generalised almost-cyclostationary process. The proposed approach performs a maximum-likelihood estimation of the CFO jointly to the detection exploiting multiple cycles, through a maximisation of the generalised likelihood ratio test. The closed-form of false alarm probability is derived highlighting that this approach represents a constant false alarm rate detector. Numerical evaluations are provided to show the correctness of the theoretical analysis and that the performance is approximatively constant for a large range of CFO values. Moreover, comparisons with existing algorithms are provided.