KEYWORDS: Orthogonal frequency division multiplexing, Signal to noise ratio, Modulation, Data modeling, Antennas, Systems modeling, Telecommunications, Multiplexing, Error analysis, Computer simulations
In this paper is investigated the performance of an uplink MIMO system when the multi-user shared access (MUSA) technique is applied. The complex spreading codes used in MUSA are created starting from the traditional PN codes that are used in the code division multiple access (CDMA) systems. We choose this approach to be sure that the obtained complex spreading codes have low correlation. The numerical results will help us conclude if our proposed method, to create complex spreading codes, is achieving the best performance when the modulated information is transmitted over a channel affected by Rayleigh fading, in an overloaded system. The results obtained by our method will be compared with the ones obtained when the complex spreading codes are created arbitrarily.
KEYWORDS: Relays, Antennas, Signal to noise ratio, Systems modeling, Receivers, Wireless communications, Telecommunications, Multiplexing, Monte Carlo methods
Our world is in a continuous evolution from all points of view, therefore there are new needs for which support must be provided and for which a series of new techniques have been proposed. In the field of wireless communications, we can talk about non-orthogonal multiple access (NOMA) technique, which is included in the 5G standard, that can offer an increased quality of service (QoS) to end users irrespective of their position within the cell or distortion factors. This paper presents a new set of complex spreading codes that fall in the coverage area of the 5G NOMA-based technique scheme. The creation of the new, aforementioned, set of complex codes starts from Walsh- Hadamard orthogonal spreading codes. Their performance will be tested using Monte Carlo Matlab simulations for bit error rate (BER) versus signal-to-noise ratio (SNR). The performance of the system will be tested in different scenarios, where the number of antennas at the receiver, the length of the complex spreading codes and the number of active users vary.
In this paper, the performance of Orthogonal Frequency-Division Multiplexing (OFDM) in a downlink Massive-MIMO system is investigated. In addition, precoding algorithms that have access to the channel state information (CSI) of all active users in the system are used to achieve the interference mitigation often carried out with the help of signal processing transformations. The numerical results will help us conclude which of the two, Zero Forcing (ZF) or Minimum Mean Square Error (MMSE) precoders, are achieving the best performance when the modulated information is transmitted over a channel affected by Rayleigh fading.
The fifth generation (5G) and future wireless networks meet the necessities of a world increasingly more dependent on mobile Internet and mobile phones. Thus, there are a series of technologies that make this possible, part of which are present in this paper. One such technology is where multiple antennas can be used for the receiver/transmitter terminals known as MIMO and evolved to Massive MIMO, where the number of antennas is much higher. Another one is represented by orthogonal frequency-division multiplexing (OFDM) used to mitigate or eliminate the inter-symbol and intra-symbol interferences. Low-density parity-check (LDPC) codes have relatively low and scalable decoding complexity. Therefore, in this paper is proposed a Massive multiuser MIMO system with Manchester source coding, LPDC channel coding and OFDM used by multiple users, when the number of antennas at the receiver varies between 8 and 12. Therefore, taking into account the afore-mentioned technologies and parameters, we analyze the quality of the information that reaches the base station (BS) using extensive Monte Carlo Matlab simulations in terms of bit error rate (BER) versus signal-to-noise ratio (SNR) for pseudorandom (PN) spreading codes, which spreads the OFDM modulated signal with or without Manchester encoding.
KEYWORDS: Orthogonal frequency division multiplexing, Modulation, Antennas, Receivers, Monte Carlo methods, Quadrature amplitude modulation, Signal to noise ratio, Transmitters
The recently implemented 4G network meets nowadays the necessities of a world in a continuous development. Among the new technologies introduced by this standard is the one in which multiple antennas are used at the receiver and at the transmitter ends (MIMO) in order to increase the overall system performances. Massive MIMO is an evolved version of the conventional MIMO that uses a significantly larger number of antennas at the transmitter / receiver. This technology will be included in the much-discussed 5G standard. Another technology that is present in 4G/5G standards is the orthogonal frequency-division multiplexing (OFDM), which is a modulation technique where the information is arranged in blocks of information symbols that are transmitted in parallel on orthogonal subcarriers, as well as new low complexity / high performances encoding techniques. In order to study the enhancement brought by these technologies, in this paper, we propose an uplink Massive MU-MIMO OFDM-based system with low-density parity-check (LDPC) coding used by multiple users which are active simultaneously, when the number of Base Station (BS) antennas varies from 10 to 100. Based on this proposed structure, the transmitter, receiver and communication channel will be simulated in Matlab/Simulink. Extensive Monte Carlo simulation are under development to evaluate the system performances in terms of Bit Error Rate (BER) as a function of Signal to Noise Ratio (SNR).
KEYWORDS: Relays, Antennas, Telecommunications, Sensors, Error analysis, Signal to noise ratio, Signal detection, Computer simulations, Receivers, Monte Carlo methods
In an uplink multiuser system in which the users are situated far enough from the base station (BS), or in which the communication is affected by fading, the use of relays can bring a plus in the quality of the information arrived at the BS. In this paper, the performance of an uplink connection for a Massive MU-MIMO system is analysed with or without relay nodes in order to see how the bit error rate metric (BER) improves when the number of antennas at the base station (BS) is increased from 10 to 100 and for different number of active users that simultaneously require mobile resources to accomplish their momentary needs. For a better evaluation of the proposed system we use, two types of relays, one based on amplifyand- forward (AF) protocol and one on decode-and-forward (DF) protocol. At the BS a maximal ratio combiner (MRC) is used to combine the signals received from users and relay, and a minimum mean-square error (MMSE) detection is applied to recover the information sent by each user. The simulations show that, by using relays, we have a significant gain, especially when the number of the active users is close with the number of antennas from the base station.
Recently, technological development imposed a rapid growth in the use of data carried by cellular services, which also implies the necessity of higher data rates and lower latency. To meet the users’ demands, it was brought into discussion a series of new data processing techniques. In this paper, we approached the MIMO technology that uses multiple antennas at the receiver and transmitter ends. To study the performances obtained by this technology, we proposed a MIMO-CDMA system, where image transmission has been used instead of random data transmission to take benefit of a larger range of quality indicators. In the simulations we increased the number of antennas, we observed how the performances of the system are modified and, based on that, we were able to make a comparison between a conventional MIMO and a Large Scale MIMO system, in terms of BER and MSSIM index, which is a metric that compares the quality of the image before transmission with the received one.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.