Signal Processing for Communication Systems
Multiple-Input Multiple-Output (MIMO) is a wireless communication technology that greatly improves data transmission and reception by using multiple antennas at both the transmitter and receiver. It is a fundamental component of modern wireless standards, enhancing data rates, boosting reliability, and increasing network efficiency. Here are the key aspects of MIMO: Overview of MIMO MIMO enables … Read more
In the previous post on Single Input Multiple Output (SIMO) models for receive diversity, various receiver diversity techniques were outlined. One of them is maximum ratio combining, the focus of the topic here. Channel model Assuming flat slow fading channel, the received signal model is given by where, is the channel impulse response, is the … Read more
In the previous post on Single Input Multiple Output (SIMO) models for receive diversity, various receiver diversity techniques were outlined. One of them is selection combining, the focus of the topic here. Channel model Assuming flat slow fading channel, the received signal model is given by where, is the channel impulse response, is the received … Read more
SIMO channel configuration is characterized by 1 transmit antenna and multiple receiver antennas (Figure 1). SIMO configuration is used to provide receive diversity, where the same information is received across independent fading channels to combat fading. When multiple copies of the same data are received across independently fading channels, the amount of fade suffered by each … Read more
As reiterated in the previous article, a MIMO system is used to increase the capacity dramatically and also to improve the quality of a communication link. Increased capacity is obtained by spatial multiplexing and increased quality is obtained by diversity techniques (Space time coding). Capacity of MIMO system over a variety of channels (AWGN, fading … Read more
Understand ergodic capacity of a SISO flat-fading system over fading channels. Model and simulate capacity curves in Matlab. Channel model In the previous post, derivation of SISO fading channel capacity was discussed. For a flat fading channel (model shown below), with the perfect knowledge of the channel at the receiver, the capacity of a SISO … Read more
As reiterated in the previous article, a MIMO system is used to increase the capacity dramatically and also to improve the quality of a communication link. Increased capacity is obtained by spatial multiplexing and increased quality is obtained by diversity techniques (Space time coding). Capacity equations of a MIMO system over a variety of channels … Read more
Two flavors of MIMO implementation – spatial multiplexing and spatial diversity – were discussed in the previous article. In that, it was mentioned that the reliability of a MIMO system is governed by diversity and the capacity of the link is governed by degrees of freedom. Channel State Information (CSI) Multiple data streams can be … Read more
The wireless communication environment is very hostile. The signal transmitted over a wireless communication link is susceptible to fading (severe fluctuations in signal level), co-channel interference, dispersion effects in time and frequency, path loss effect, etc. On top of these woes, the limited availability of bandwidth posses a significant challenge to a designer in designing … Read more
Regarded as a breakthrough in wireless communication system design, multiple antenna systems fuel the ever increasing data rate requirements of advanced technologies like UMTS, LTE, WLAN etc. Multiple antenna systems come in different flavors and are generally referred as Multiple Input Multiple Output systems (MIMO). In a series of articles, I intend to cover various … Read more